Triple
T499568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Mara |
E10370
|
entity |
| Predicate | televisionDebut |
P3279
|
FINISHED |
| Object | Law & Order (guest appearance) |
—
|
LITERAL 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 (guest appearance) | Statement: [Kate Mara, televisionDebut, Law & Order (guest appearance)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: televisionDebut Context triple: [Kate Mara, televisionDebut, Law & Order (guest appearance)]
-
A.
originallyAiredOn
Indicates the date or time when a media work (such as a TV episode, radio show, or broadcast) was first publicly aired.
-
B.
firstTelevisionBroadcast
Indicates that the subject is the entity responsible for the earliest or inaugural television broadcast of the object.
-
C.
firstAired
Indicates the date on which something (such as a show, episode, or broadcast content) was first aired or publicly transmitted.
-
D.
filmDebut
Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
-
E.
televisionShow
chosen
Indicates that one entity is a television show associated with, or featured in relation to, another entity.
- F. None of above.
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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f119b14c8190a5a6b119579c2682 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edfa87cc8190a77c726a5a55b7d9 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.