Triple
T15927963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Low Pros (production contributions) |
E386250
|
entity |
| Predicate | associatedWithArtist |
P5936
|
FINISHED |
| Object | Que |
E1069172
|
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: Que | Statement: [Low Pros (production contributions), associatedWithArtist, Que]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Que Context triple: [Low Pros (production contributions), associatedWithArtist, Que]
-
A.
Que
Que was an Iron Age Neo-Hittite kingdom located in Cilicia in southeastern Anatolia, known from Assyrian records and archaeological remains.
-
B.
Que
chosen
Que is a musical artist best known for performing the track "Loyal."
-
C.
QUE
QUE is the standard abbreviation used for the Quebec Remparts, a major junior ice hockey team in the Quebec Major Junior Hockey League.
-
D.
QUE
QUE is the station code for Queen station, a public transit stop in Toronto's subway system.
-
E.
Q
Q is a recurring comedic character from the James Bond film series, known as the eccentric head of MI6's gadget and technology division.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156872964819083a2fb9f86df61ba |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5b0833081909668c042234b5b75 |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:52 a.m.