Triple
T9214425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Fenêtre ouverte |
E221206
|
entity |
| Predicate | hasIronicTwist |
P71901
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [La Fenêtre ouverte, hasIronicTwist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIronicTwist Context triple: [La Fenêtre ouverte, hasIronicTwist, true]
-
A.
hasIronicMeaning
chosen
Indicates that something conveys a meaning opposite to or incongruent with its literal expression, creating an ironic effect.
-
B.
hasTragicEnding
Indicates that the event, story, or situation concludes with a sorrowful, disastrous, or otherwise deeply unfortunate outcome.
-
C.
hasMystery
Indicates that one entity possesses, contains, or is associated with something unknown, secret, or unexplained in relation to another entity.
-
D.
hasEnigmaticCharacter
Indicates that something possesses a mysterious, puzzling, or difficult-to-interpret quality or nature.
-
E.
hasUnreliableNarrator
Indicates that the story is told by a narrator whose account cannot be fully trusted due to bias, limited knowledge, deception, or instability.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda06bf80819094c6e74b4b6a31e4 |
completed | April 1, 2026, 8:40 a.m. |
| PD | Predicate disambiguation | batch_69cc660ce23c81909c7bbe10f4a05f36 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:27 p.m.