Triple
T6578173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ann Elizabeth Thompson Pershing |
E157222
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Pershing |
E142899
|
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: Pershing | Statement: [Ann Elizabeth Thompson Pershing, familyName, Pershing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pershing Context triple: [Ann Elizabeth Thompson Pershing, familyName, Pershing]
-
A.
Pershing
chosen
Pershing is a surname most notably associated with John J. Pershing, the prominent American general who led the American Expeditionary Forces in World War I.
-
B.
Pulaski
Pulaski is a Chicago Transit Authority Blue Line rapid transit station serving the city's West Side.
-
C.
Sherman
Sherman is a city in north-central Texas that serves as a regional hub for commerce and transportation in the Texoma area.
-
D.
Sherman
Sherman is the bumbling yet kind-hearted scientist protagonist portrayed by Eddie Murphy in the comedy film "The Nutty Professor."
-
E.
Sherman
Sherman is a surname of English origin borne by numerous notable individuals across politics, military history, and the arts.
- 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_69c6882b3a108190b3a9eb343ae4162c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae74fd90819091d67eec6381d5e0 |
completed | March 27, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cba5cc708190a8748160a7878b8f |
completed | March 27, 2026, 6:25 p.m. |
Created at: March 27, 2026, 1:54 p.m.