Triple
T14514146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jesus in "El ángel exterminador" |
E340473
|
entity |
| Predicate | trappedIn |
P114541
|
FINISHED |
| Object | dining room |
—
|
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: dining room | Statement: [Jesus in "El ángel exterminador", trappedIn, dining room]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trappedIn Context triple: [Jesus in "El ángel exterminador", trappedIn, dining room]
-
A.
trappedDuring
Indicates that one entity is confined, caught, or immobilized while a specified event or situation is occurring.
-
B.
trap
Indicates that an entity captures, confines, or ensnares another entity, typically preventing its escape or movement.
-
C.
numberOfPeopleTrapped
Indicates the count of individuals who are currently trapped in a given situation or location.
-
D.
caughtBetween
Indicates being simultaneously subject to opposing forces, demands, or sides, unable to fully align with or escape either.
-
E.
heldCaptive
Indicates that one entity is being forcibly confined or restrained by another, preventing their freedom of movement or escape.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a6d82988190b6f957012bcc63d4 |
completed | April 14, 2026, 7:50 p.m. |
| PD | Predicate disambiguation | batch_69de5c4ccba08190a988bfda0bc9f5cb |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:21 a.m.