Triple
T16732959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William A. Blakley |
E406637
|
entity |
| Predicate | appointedBy |
P257
|
FINISHED |
| Object | Price Daniel |
E802330
|
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: Price Daniel | Statement: [William A. Blakley, appointedBy, Price Daniel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Price Daniel Context triple: [William A. Blakley, appointedBy, Price Daniel]
-
A.
Price Daniel
chosen
Price Daniel was a mid-20th-century Texas politician who served as governor, U.S. senator, and state attorney general.
-
B.
دانيال
دانيال هو اسم علم مذكر شائع في العالم العربي والإسلامي، ذو أصول دينية وتاريخية مرتبطة بالنبي دانيال.
-
C.
Daniels
Daniels is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
-
D.
Denny
Denny is a small town in central Scotland, located in the Falkirk council area.
-
E.
Denny
Denny is the surname of Reginald Denny, an English-born actor and World War I aviator who became a notable Hollywood film and television performer.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c3748d08190a57ae40f54aa63c4 |
completed | April 18, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d4c723c8190ad92628f4164d11c |
completed | May 10, 2026, 2:59 p.m. |
Created at: April 10, 2026, 5:20 a.m.