Triple
T38364753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eyes Without a Face |
E892406
|
entity |
| Predicate | abductorCharacter |
P190465
|
FINISHED |
| Object | Dr. Génessier |
—
|
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: Dr. Génessier | Statement: [Eyes Without a Face, abductorCharacter, Dr. Génessier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: abductorCharacter Context triple: [Eyes Without a Face, abductorCharacter, Dr. Génessier]
-
A.
allyOfCharacter
Indicates that one character maintains an alliance or supportive partnership with another character.
-
B.
eraCharacter
Indicates that a character is associated with, or belongs to, a particular historical or fictional era.
-
C.
exteriorCharacter
Indicates a relationship where one entity’s outward or visible qualities, features, or appearance are being characterized or described.
-
D.
animatedCharacter
Indicates that an entity is a fictional character depicted through animation rather than live action.
-
E.
exposedByCharacter
Indicates that one character reveals, uncovers, or discloses something about another character or their actions.
- F. None of above. chosen
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_69f76e47cb4c8190bdd92cd1db59c0c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcc7a4d7f881908b43b960911b81e9 |
completed | May 7, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69fcc589720c819089c8f500fea3c86a |
completed | May 7, 2026, 5:02 p.m. |
| PDg | Predicate description generation | batch_69fcc7a42f68819081d6ec8bb6b53438 |
completed | May 7, 2026, 5:11 p.m. |
Created at: May 3, 2026, 4:31 p.m.