Triple
T7900100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotel Lobby |
E183427
|
entity |
| Predicate | narrativeCharacteristic |
P79666
|
FINISHED |
| Object | ambiguous narrative |
—
|
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: ambiguous narrative | Statement: [Hotel Lobby, narrativeCharacteristic, ambiguous narrative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeCharacteristic Context triple: [Hotel Lobby, narrativeCharacteristic, ambiguous narrative]
-
A.
narrative
Indicates that one entity tells, presents, or conveys a story or sequence of events about another entity or situation.
-
B.
narrativeType
Indicates the specific kind or category of narrative (e.g., genre, structural form, or storytelling mode) associated with an entity.
-
C.
narrativeCharacter
Indicates that one entity functions as a character within the narrative or story associated with another entity.
-
D.
narrativeStyle
Indicates how a narrative is told, such as the point of view, tone, and structural approach used to present a story or account.
-
E.
narrativeStrategy
Indicates the method or approach used to structure, present, or convey a story or sequence of events.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a3dc2208190a6fea93b60b8daca |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7882b048190baa333af9f698590 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:02 p.m.