Triple
T4969486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asa Philip Randolph |
E111611
|
entity |
| Predicate | givenNameUsage |
P12827
|
FINISHED |
| Object | Asa is his first name |
E111611
|
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: Asa is his first name | Statement: [Asa Philip Randolph, givenNameUsage, Asa is his first name]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asa is his first name Context triple: [Asa Philip Randolph, givenNameUsage, Asa is his first name]
-
A.
Asher
Asher is a biblical figure, one of the twelve sons of Jacob and the ancestor of the Israelite Tribe of Asher.
-
B.
Asa
chosen
Asa is the given first name of A. Philip Randolph, the prominent American civil rights leader and labor organizer.
-
C.
Asa
Asa is a local government area in Kwara State, Nigeria, known for its predominantly rural communities and agricultural activities.
-
D.
Asa
Asa was a biblical king of Judah known for religious reforms and efforts to abolish idolatry in his kingdom.
-
E.
Aš
Aš is a town in the Karlovy Vary Region of the Czech Republic, located near the German border and known for its textile industry and borderland history.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd721221b88190916feb9b4f049195 |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81f749fc8190ad4dc68f7e2086b1 |
completed | March 21, 2026, 11:33 a.m. |
Created at: March 20, 2026, 1:32 p.m.