Triple
T28262013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frou-Frou |
E712605
|
entity |
| Predicate | placeOfFirstSignificantReception |
P177122
|
FINISHED |
| Object | Paris |
—
|
NE NERFINISHED |
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: Paris | Statement: [Frou-Frou, placeOfFirstSignificantReception, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placeOfFirstSignificantReception Context triple: [Frou-Frou, placeOfFirstSignificantReception, Paris]
-
A.
dateOfFirstTransatlanticTransmission
Indicates the date on which the first transatlantic transmission between the related entities took place.
-
B.
firstTelecastOn
Indicates the date or event on which something, typically a program or broadcast, was first shown on television.
-
C.
locationOfFirstCommercialUse
Indicates the place where something was first used commercially.
-
D.
firstBroadcastInCountry
Indicates that a work (such as a program or broadcast) was first aired or transmitted in a specified country.
-
E.
firstTelevisionNetwork
Indicates that one entity is the earliest or original television network associated with another entity (such as a person, show, or organization).
- 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_69efb5207eb08190827e4c34048030b1 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f854486c81909396d944a55e03ab |
completed | May 3, 2026, 7:25 a.m. |
Created at: April 27, 2026, 11:12 p.m.