Triple
T4903722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mt. Lebanon |
E109863
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Upper St. Clair |
E148043
|
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: Upper St. Clair | Statement: [Mt. Lebanon, adjacentTo, Upper St. Clair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Upper St. Clair Context triple: [Mt. Lebanon, adjacentTo, Upper St. Clair]
-
A.
Upper St. Clair
chosen
Upper St. Clair is a suburban township in southwestern Pennsylvania known for its affluent residential character and highly ranked public school system.
-
B.
Bethel Park
Bethel Park is a suburban municipality in southwestern Pennsylvania, located just south of Pittsburgh.
-
C.
Aliquippa
Aliquippa is a small industrial city in western Pennsylvania known historically for its steel production and location along the Ohio River.
-
D.
Penn Hills
Penn Hills is a suburban municipality in western Pennsylvania, located just east of Pittsburgh in Allegheny County.
-
E.
Wynnewood
Wynnewood is a suburban community in Pennsylvania’s Main Line area, known for its residential neighborhoods and commuter access to Philadelphia.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e6fdeac81909092f51ae40ad20e |
completed | March 20, 2026, 3:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fd6ce008190ae7897bc58a2e786 |
completed | March 21, 2026, 10:15 a.m. |
Created at: March 20, 2026, 1:29 p.m.