Triple
T14730642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Fitch Cooper |
E346063
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Fitch |
E533020
|
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: Fitch | Statement: [Dr. Fitch Cooper, givenName, Fitch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fitch Context triple: [Dr. Fitch Cooper, givenName, Fitch]
-
A.
Fitch
chosen
Fitch is a surname of English origin borne by various notable individuals across fields such as finance, academia, and the arts.
-
B.
Fitch Ratings
Fitch Ratings is a major global credit rating agency that evaluates the creditworthiness of governments, corporations, and financial instruments worldwide.
-
C.
Moody's
Moody's is a leading global credit rating agency and financial services company known for assessing the creditworthiness of governments, corporations, and financial instruments.
-
D.
Standard & Poor's
Standard & Poor's is a major American financial services company best known for its stock market indices and credit ratings.
-
E.
FBR
FBR is Pakistan’s federal government agency responsible for tax collection, enforcement of fiscal laws, and formulation of revenue-related policies.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec26311c8819093a81ff0fa43b33b |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb89ea388190b356df74e36023f7 |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.