Triple
T18190885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Cote |
E435528
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Cote
Cote is a surname most notably borne by American businessman David Cote, former CEO of Honeywell.
|
E1311005
|
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: Cote | Statement: [David Cote, familyName, Cote]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cote Context triple: [David Cote, familyName, Cote]
-
A.
Cote
Cote is a small rural settlement in Oxfordshire, England, known for its historic church and traditional village character.
-
B.
Côte Brune
Côte Brune is a renowned, steeply terraced northern Rhône vineyard area within Côte-Rôtie, famed for producing structured, long-lived Syrah-based red wines.
-
C.
Côte d’Argent
Côte d’Argent is a long stretch of sandy beaches and dunes along France’s southwestern Atlantic coast, popular for surfing, seaside resorts, and natural coastal landscapes.
-
D.
Guichen
Guichen was a French admiral, Luc Urbain de Bouëxic, comte de Guichen, noted for commanding French naval forces during the American Revolutionary War.
-
E.
Côte Bleue
Côte Bleue is a scenic stretch of Mediterranean coastline in southern France, west of Marseille, known for its calanques, beaches, and picturesque seaside villages.
- 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: Cote Triple: [David Cote, familyName, Cote]
Generated description
Cote is a surname most notably borne by American businessman David Cote, former CEO of Honeywell.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cote Target entity description: Cote is a surname most notably borne by American businessman David Cote, former CEO of Honeywell.
-
A.
Cote
Cote is a small rural settlement in Oxfordshire, England, known for its historic church and traditional village character.
-
B.
Côte Brune
Côte Brune is a renowned, steeply terraced northern Rhône vineyard area within Côte-Rôtie, famed for producing structured, long-lived Syrah-based red wines.
-
C.
Côte d’Argent
Côte d’Argent is a long stretch of sandy beaches and dunes along France’s southwestern Atlantic coast, popular for surfing, seaside resorts, and natural coastal landscapes.
-
D.
Guichen
Guichen was a French admiral, Luc Urbain de Bouëxic, comte de Guichen, noted for commanding French naval forces during the American Revolutionary War.
-
E.
Côte Bleue
Côte Bleue is a scenic stretch of Mediterranean coastline in southern France, west of Marseille, known for its calanques, beaches, and picturesque seaside villages.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0cf0d7c81908ce0386c52ef601d |
completed | April 19, 2026, 2:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0398090dc0819082d4bd4df858f847 |
completed | May 12, 2026, 9:13 p.m. |
| NEDg | Description generation | batch_6a0399663b388190b7227e1dca0040a7 |
completed | May 12, 2026, 9:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0399ff18948190ad2c3fbe1e5986cc |
completed | May 12, 2026, 9:22 p.m. |
Created at: April 10, 2026, 10:31 a.m.