Triple
T20173800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justin James Watt |
E492037
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Justin |
—
|
NE NERFINISHED |
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: Justin | Statement: [Justin James Watt, givenName, Justin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Justin Context triple: [Justin James Watt, givenName, Justin]
-
A.
Justin
Justin is a character in the novel "Falling Man," which explores the aftermath of the September 11 attacks and their impact on personal and collective identity.
-
B.
Justin
Justin is a central character in the 1997 science fiction horror film "Event Horizon," serving as one of the crew members who experiences the ship’s disturbing and reality-warping effects.
-
C.
Justin
chosen
Justin is the first name of J. J. Watt, the prominent American football defensive end known for his standout NFL career with the Houston Texans.
-
D.
Justin
Justin is a small suburban town within the Dallas–Fort Worth metropolitan area in Texas.
-
E.
Justin
Justin was a Roman historian and epitomator best known for his abridged version of Pompeius Trogus’s universal history, which includes accounts of famous legends such as the Gordian Knot.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6684a33688190b22cfc16907e76bc |
completed | April 20, 2026, 5:54 p.m. |
Created at: April 11, 2026, 11:36 p.m.