Triple
T2178055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegheny, Pennsylvania |
E48576
|
entity |
| Predicate | populationBeforeAnnexation |
P23346
|
FINISHED |
| Object | about 150000 |
—
|
LITERAL 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: about 150000 | Statement: [Allegheny, Pennsylvania, populationBeforeAnnexation, about 150000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationBeforeAnnexation Context triple: [Allegheny, Pennsylvania, populationBeforeAnnexation, about 150000]
-
A.
annexedInYear
Indicates that one entity was formally annexed or incorporated into another in the specified calendar year.
-
B.
northernPartAnnexedBy
Indicates that the northern portion of an entity has been taken over and incorporated into another entity.
-
C.
formerPopulation
chosen
Indicates that an entity once had a certain population value or size during a past time period but no longer does.
-
D.
wasAnnexedInPartition
Indicates that a territory or entity was incorporated into another as a result of a formal partition of land or political division.
-
E.
annexationDate
Indicates the date on which one entity formally annexed or incorporated another entity into its territory or jurisdiction.
- F. None of above.
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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.