Triple
T23503335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Coats |
E571914
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Coats |
E1423299
|
NE FINISHED |
How this triple was built (2 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: Coats | Statement: [Thomas Coats, familyName, Coats]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coats Context triple: [Thomas Coats, familyName, Coats]
-
A.
Coats
Coats is a well-known global brand specializing in industrial threads, yarns, and related textile products.
-
B.
Coats
chosen
Coats is a surname of English and Scottish origin borne by various notable individuals, including figures in politics, science, and the arts.
-
C.
COATS
COATS is the abbreviated name for the Cadet Organizations Administration and Training Service, a Canadian Armed Forces component responsible for supporting and training youth cadet programs.
-
D.
Socks
Socks is a fictional character, likely an animal companion or pet, featured in the "Dear Socks, Dear Buddy" book.
-
E.
Maglie
Maglie is a historic town in Italy’s Apulia region, known for its Baroque architecture and role as a commercial and cultural center in the Salento area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a8fe1e3081908c4a9df4e137b9b3 |
completed | April 29, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c8275e2bc8190a908d41a9824f2f8 |
completed | May 19, 2026, 3:32 p.m. |
Created at: April 17, 2026, 6:06 p.m.