Triple
T1908985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis Place |
E38064
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Place
Place is an English surname borne by various notable figures, including the 18th–19th century social reformer Francis Place.
|
E211908
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Place | Statement: [Francis Place, familyName, Place]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Place Context triple: [Francis Place, familyName, Place]
-
A.
Location
The Location header field is an HTTP response header used to indicate the URL to which a client should be redirected or where a newly created resource can be found.
-
B.
Lage
Lage is the surname of Carlos Lage Dávila, a prominent Cuban politician who served as Vice President of the Council of State and was considered a key figure in the country’s government in the early 2000s.
-
C.
Ville
Ville is a common Finnish male given name, especially prevalent in the late 20th century.
-
D.
Places API
Places API is a Google Maps web service that provides detailed information about geographic locations, including place search, details, photos, and autocomplete functionality for applications.
-
E.
LOC
LOC is the commonly used abbreviation for the Library of Congress, the national library of the United States and one of the largest libraries in the world.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Place Triple: [Francis Place, familyName, Place]
Generated description
Place is an English surname borne by various notable figures, including the 18th–19th century social reformer Francis Place.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Place Target entity description: Place is an English surname borne by various notable figures, including the 18th–19th century social reformer Francis Place.
-
A.
Location
The Location header field is an HTTP response header used to indicate the URL to which a client should be redirected or where a newly created resource can be found.
-
B.
Lage
Lage is the surname of Carlos Lage Dávila, a prominent Cuban politician who served as Vice President of the Council of State and was considered a key figure in the country’s government in the early 2000s.
-
C.
Ville
Ville is a common Finnish male given name, especially prevalent in the late 20th century.
-
D.
Places API
Places API is a Google Maps web service that provides detailed information about geographic locations, including place search, details, photos, and autocomplete functionality for applications.
-
E.
LOC
LOC is the commonly used abbreviation for the Library of Congress, the national library of the United States and one of the largest libraries in the world.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1b55edc8190bce8ac97196939a9 |
completed | March 7, 2026, 5:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeafdad3c8190be7aeaed8bdeac43 |
completed | March 8, 2026, 9:32 p.m. |
| NEDg | Description generation | batch_69adeb7075f48190a27b5039c3b4691e |
completed | March 8, 2026, 9:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adec37a4f88190961edf8f9c81773c |
completed | March 8, 2026, 9:37 p.m. |
Created at: March 4, 2026, 7:35 p.m.