Triple
T3968986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robin Hood (1973 film) |
E92282
|
entity |
| Predicate | portraysLittleJohnAs |
P33556
|
FINISHED |
| Object | bear |
—
|
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: bear | Statement: [Robin Hood (1973 film), portraysLittleJohnAs, bear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysLittleJohnAs Context triple: [Robin Hood (1973 film), portraysLittleJohnAs, bear]
-
A.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
B.
portraysDonJuanAs
Indicates that a subject represents or depicts Don Juan in a particular manner, role, or characterization.
-
C.
portraysFictionalEntity
chosen
Indicates that one entity depicts, represents, or plays the role of a fictional character or figure.
-
D.
youngerVersionPortrayedBy
Indicates that one person portrays a younger version of another person, typically in a film, television show, or similar narrative work.
-
E.
playedBy
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_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.