Triple
T30070957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 100 Girls |
E764180
|
entity |
| Predicate | characterPlayedBy Katherine Heigl |
P9616
|
FINISHED |
| Object | Arlene |
—
|
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: Arlene | Statement: [100 Girls, characterPlayedBy Katherine Heigl, Arlene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedBy Katherine Heigl Context triple: [100 Girls, characterPlayedBy Katherine Heigl, Arlene]
-
A.
characterPlayedBy Emmanuelle Chriqui
Indicates that the role or character in question is portrayed or acted by Emmanuelle Chriqui.
-
B.
characterVoicedBy Paget Brewster
Indicates that a character is voiced by Paget Brewster.
-
C.
characterPlayedBy Jill Clayburgh
Indicates that the specified character is portrayed or acted by Jill Clayburgh.
-
D.
characterPlayedBy_MichelleRyan
Indicates that the subject is a character portrayed or played by Michelle Ryan.
-
E.
playedBy
chosen
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
- 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_69f2247221388190a13a22c47094a0ef |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: April 29, 2026, 7 p.m.