Triple
T6524940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodie Flowers |
E151278
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | FIRST |
E28624
|
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: FIRST | Statement: [Woodie Flowers, memberOf, FIRST]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FIRST Context triple: [Woodie Flowers, memberOf, FIRST]
-
A.
FIRST
chosen
FIRST (For Inspiration and Recognition of Science and Technology) is an international youth organization that runs robotics competitions and programs to inspire students’ interest and participation in science, technology, engineering, and math.
-
B.
Unua
Unua is an Oceanic language spoken by a small community in Vanuatu.
-
C.
IRST
IRST (Iran Standard Time) is the time zone used throughout Iran, set 3.5 hours ahead of Coordinated Universal Time (UTC+3:30).
-
D.
First of the First
First of the First is the nickname of the 1st Battalion, 1st Marines, a storied infantry battalion of the United States Marine Corps known for its long combat history.
-
E.
Up First
Up First is NPR's daily morning news podcast that delivers a concise roundup of the day's top stories.
- 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ad9831f88190a2b64cf6bc8c9a11 |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d52372d08190a98c611dabc27c85 |
completed | March 27, 2026, 7:06 p.m. |
Created at: March 27, 2026, 1:45 p.m.