Triple
T32606588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerard Francis Conway |
E833536
|
entity |
| Predicate | notableTelevisionCredit |
P40639
|
FINISHED |
| Object | Law & Order |
E163933
|
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: Law & Order | Statement: [Gerard Francis Conway, notableTelevisionCredit, Law & Order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableTelevisionCredit Context triple: [Gerard Francis Conway, notableTelevisionCredit, Law & Order]
-
A.
notableCharacterPortrayal
Indicates that an entity is recognized for its portrayal or depiction of a particular character, typically in a performance or narrative work.
-
B.
notableSeriesCharacter
Indicates that an entity is a significant or well-known character appearing in a particular series.
-
C.
notableTelevisionProduction
chosen
Indicates that the subject is significantly associated with the creation or production of the referenced television work.
-
D.
notableAppearanceIn
Indicates that an entity is prominently featured or plays a significant role in a particular work, event, or context.
-
E.
notableSeriesContribution
Indicates that an entity has made a significant or distinguished contribution to a particular series (such as a publication, show, or collection).
- F. None of above.
Provenance (4 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3486165d708190a9d5085fcc3c004b |
completed | June 18, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:05 a.m.