Triple
T3968987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robin Hood (1973 film) |
E92282
|
entity |
| Predicate | portraysMaidMarianAs |
P33556
|
FINISHED |
| Object | vixen |
—
|
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: vixen | Statement: [Robin Hood (1973 film), portraysMaidMarianAs, vixen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysMaidMarianAs Context triple: [Robin Hood (1973 film), portraysMaidMarianAs, vixen]
-
A.
portraysFictionalEntity
chosen
Indicates that one entity depicts, represents, or plays the role of a fictional character or figure.
-
B.
secondLadyTo
Indicates that one person holds the position or role of second lady in relation to another person or office.
-
C.
accusedCharacterPortrayedBy
Indicates that a particular actor or performer plays the role of the character who is accused within a given work.
-
D.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
E.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaca33e4819091957c7915857a42 |
completed | March 9, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69aef8f252b081909749d40440d372b2 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:32 p.m.