Triple
T580833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan Howard |
E15052
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Howard |
E18403
|
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: Howard | Statement: [Ryan Howard, familyName, Howard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Context triple: [Ryan Howard, familyName, Howard]
-
A.
Howard
chosen
Howard is a volume series of early U.S. Supreme Court case reports compiled by Benjamin Chew Howard, later incorporated into the official United States Reports.
-
B.
Howard
Howard is the middle name of Edwin H. Armstrong, the pioneering American electrical engineer and inventor of FM radio.
-
C.
Johnson
Johnson is a common English surname borne by numerous notable individuals across politics, arts, sports, and other fields.
-
D.
Wilson
Wilson is a common English-language surname borne by numerous notable figures across fields such as science, politics, sports, and the arts.
-
E.
Clinton
Clinton is a prominent American political surname most famously associated with Hillary Clinton, the former U.S. Secretary of State, senator, and First Lady.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b82b5248190ac863407e8207a3b |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5216c43148190961ff8cea8305b7e |
completed | March 2, 2026, 5:34 a.m. |
Created at: March 1, 2026, 7:33 p.m.