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.