Triple
T14413291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skiptrace |
E357383
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Nathan Wang |
E571146
|
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: Nathan Wang | Statement: [Skiptrace, musicBy, Nathan Wang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Wang Context triple: [Skiptrace, musicBy, Nathan Wang]
-
A.
Nathan Wang
chosen
Nathan Wang is an American composer known for scoring numerous films and television shows, often blending orchestral and contemporary styles.
-
B.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
C.
Garrett Wang
Garrett Wang is an American actor best known for playing Ensign Harry Kim on the television series Star Trek: Voyager.
-
D.
Izaac Wang
Izaac Wang is an American child actor best known for voicing Boun in Disney's animated film "Raya and the Last Dragon."
-
E.
Daniel Zhang
Daniel Zhang is a Chinese business executive best known for leading Alibaba Group through a major period of global expansion and for creating the Singles’ Day shopping festival.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd552858208190ba1550e7c1176a2a |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.