Triple
T19903210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Gambel |
E478345
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Gambel
Gambel is a surname most notably associated with American naturalist William Gambel, after whom several North American bird and plant species are named.
|
E1401686
|
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: Gambel | Statement: [William Gambel, familyName, Gambel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gambel Context triple: [William Gambel, familyName, Gambel]
-
A.
Gullett
Gullett is a surname most notably associated with former Major League Baseball pitcher Don Gullett.
-
B.
Ogilbee
Ogilbee is a Scottish surname associated with Clan Ogilvy, a historic Highland clan.
-
C.
Pinon
Pinon is a French surname most notably associated with actor Dominique Pinon, known for his distinctive roles in films by directors like Jean-Pierre Jeunet.
-
D.
Bivins
Bivins is a surname most notably associated with Michael Bivins, an American singer, rapper, and music executive known for his work with New Edition and Bell Biv DeVoe.
-
E.
Griscom
Griscom is a surname most notably associated with Elizabeth Griscom, better known as Betsy Ross, the American upholsterer and flag maker linked to the creation of the first U.S. flag.
- 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: Gambel Triple: [William Gambel, familyName, Gambel]
Generated description
Gambel is a surname most notably associated with American naturalist William Gambel, after whom several North American bird and plant species are named.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gambel Target entity description: Gambel is a surname most notably associated with American naturalist William Gambel, after whom several North American bird and plant species are named.
-
A.
Gullett
Gullett is a surname most notably associated with former Major League Baseball pitcher Don Gullett.
-
B.
Ogilbee
Ogilbee is a Scottish surname associated with Clan Ogilvy, a historic Highland clan.
-
C.
Pinon
Pinon is a French surname most notably associated with actor Dominique Pinon, known for his distinctive roles in films by directors like Jean-Pierre Jeunet.
-
D.
Bivins
Bivins is a surname most notably associated with Michael Bivins, an American singer, rapper, and music executive known for his work with New Edition and Bell Biv DeVoe.
-
E.
Griscom
Griscom is a surname most notably associated with Elizabeth Griscom, better known as Betsy Ross, the American upholsterer and flag maker linked to the creation of the first U.S. flag.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65944c55481909b54a8f9a9c087d6 |
completed | April 20, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ea473de88190aecf750fe536a8b3 |
completed | May 16, 2026, 3:53 a.m. |
| NEDg | Description generation | batch_6a07ec3b2c088190b98bd03d132e1b4e |
completed | May 16, 2026, 4:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07ecb5ec708190bc79a1be73f746d9 |
completed | May 16, 2026, 4:04 a.m. |
Created at: April 10, 2026, 1:52 p.m.