Triple
T9450111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip M. Landrum |
E227865
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Landrum
Landrum is a surname most notably associated with Philip M. Landrum, an American politician who served as a U.S. Representative from Georgia.
|
E799515
|
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: Landrum | Statement: [Philip M. Landrum, familyName, Landrum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landrum Context triple: [Philip M. Landrum, familyName, Landrum]
-
A.
Acoyte
Acoyte is a station on Buenos Aires’ historic Line A subway, serving the Caballito neighborhood in Argentina’s capital.
-
B.
Darlington
Darlington is a surname of English origin borne by various notable individuals across fields such as engineering, science, and public life.
-
C.
Darlington
Darlington is a market town and borough in County Durham, England, historically known for its pioneering role in railway development.
-
D.
Darlington
Darlington is a civil parish in New South Wales, Australia, that includes the locality of Darlington Point.
-
E.
Darlington
Darlington is a residential neighborhood in the city of Pawtucket, known as one of the oldest and most densely populated areas in Rhode Island.
- 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: Landrum Triple: [Philip M. Landrum, familyName, Landrum]
Generated description
Landrum is a surname most notably associated with Philip M. Landrum, an American politician who served as a U.S. Representative from Georgia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Landrum Target entity description: Landrum is a surname most notably associated with Philip M. Landrum, an American politician who served as a U.S. Representative from Georgia.
-
A.
Acoyte
Acoyte is a station on Buenos Aires’ historic Line A subway, serving the Caballito neighborhood in Argentina’s capital.
-
B.
Darlington
Darlington is a surname of English origin borne by various notable individuals across fields such as engineering, science, and public life.
-
C.
Darlington
Darlington is a market town and borough in County Durham, England, historically known for its pioneering role in railway development.
-
D.
Darlington
Darlington is a civil parish in New South Wales, Australia, that includes the locality of Darlington Point.
-
E.
Darlington
Darlington is a residential neighborhood in the city of Pawtucket, known as one of the oldest and most densely populated areas in Rhode Island.
- 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f6649a48190b6844daa6202efe5 |
completed | April 1, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d11070e91c8190bd793126049ead27 |
completed | April 4, 2026, 1:21 p.m. |
| NEDg | Description generation | batch_69d111113c5c81909ff654734b211753 |
completed | April 4, 2026, 1:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d111ab40a48190bb77c1cf80ef87a8 |
completed | April 4, 2026, 1:27 p.m. |
Created at: March 30, 2026, 7:51 p.m.