Triple
T18676944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Jones |
E456623
|
entity |
| Predicate | teamCity |
P7424
|
FINISHED |
| Object | Pittsburgh |
—
|
NE NERFINISHED |
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: Pittsburgh | Statement: [Mike Jones, teamCity, Pittsburgh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pittsburgh Context triple: [Mike Jones, teamCity, Pittsburgh]
-
A.
Pittsburg
Pittsburg is an industrial and residential city in Contra Costa County in the San Francisco Bay Area of California.
-
B.
Pittsburgh, Pennsylvania
chosen
Pittsburgh, Pennsylvania is a major U.S. city in western Pennsylvania known for its historic steel industry, numerous bridges, and strong educational and technology sectors.
-
C.
PGH
PGH is the IATA airport code for Pantnagar Airport, a regional airport serving the city of Pantnagar in Uttarakhand, India.
-
D.
PGH
PGH is the Philippine General Hospital, a major government-owned tertiary referral and teaching hospital in Manila affiliated with the University of the Philippines.
-
E.
Duquesne, Pennsylvania
Duquesne, Pennsylvania is a small industrial city along the Monongahela River near Pittsburgh, historically known as a major steel-producing community in the American Rust Belt.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b66680819082a268f1bf857db5 |
completed | April 19, 2026, 10:27 p.m. |
Created at: April 10, 2026, 11:48 a.m.