Triple
T3968988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robin Hood (1973 film) |
E92282
|
entity |
| Predicate | portraysPrinceJohnAs |
P53229
|
FINISHED |
| Object | lion |
—
|
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: lion | Statement: [Robin Hood (1973 film), portraysPrinceJohnAs, lion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysPrinceJohnAs Context triple: [Robin Hood (1973 film), portraysPrinceJohnAs, lion]
-
A.
viewOfPrince
Indicates a visual representation or perspective specifically depicting the prince.
-
B.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
C.
portraysDonJuanAs
Indicates that a subject represents or depicts Don Juan in a particular manner, role, or characterization.
-
D.
coPrince
Indicates a relationship in which two or more individuals simultaneously share and exercise the rank and authority of prince over the same domain or polity.
-
E.
portrayedLordByronAs
Indicates that one entity depicted or represented Lord Byron in some medium or context.
- 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_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. |
| PDg | Predicate description generation | batch_69aefac8f7a48190b065487ce090eaf2 |
completed | March 9, 2026, 4:52 p.m. |
Created at: March 9, 2026, 3:32 p.m.