Triple
T4850367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pfizer |
E108398
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object | PFE |
E108398
|
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: PFE | Statement: [Pfizer, tickerSymbol, PFE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PFE Context triple: [Pfizer, tickerSymbol, PFE]
-
A.
PFA
PFA is a Danish pension fund that invests in large infrastructure projects such as offshore wind farms.
-
B.
PFA
PFA is the Professional Footballers' Association, the trade union and representative body for professional footballers in England and Wales.
-
C.
Pfizer
chosen
Pfizer is a major American multinational pharmaceutical and biotechnology corporation known for developing a wide range of prescription medicines and vaccines, including one of the first widely used COVID-19 vaccines.
-
D.
Abbott
Abbott is a masculine given name of English origin, historically associated with clerical or religious roles.
-
E.
Roche
Roche is a major Swiss multinational healthcare company and one of the world’s leading pharmaceutical and diagnostics firms.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d1e5cf08190bd6b6a524748f170 |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cdefda8819095fbc04446bf32f5 |
completed | March 21, 2026, 8:54 a.m. |
Created at: March 20, 2026, 1:25 p.m.