Triple
T25983309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iver Heath |
E646127
|
entity |
| Predicate | hasNearbyFilmStudio |
P177094
|
FINISHED |
| Object | Pinewood Studios |
—
|
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: Pinewood Studios | Statement: [Iver Heath, hasNearbyFilmStudio, Pinewood Studios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyFilmStudio Context triple: [Iver Heath, hasNearbyFilmStudio, Pinewood Studios]
-
A.
hasNeighboringStudios
Indicates that one studio is located adjacent to or in close proximity to another studio.
-
B.
hasStudio
Indicates that an entity (such as a film, game, or production) is associated with or produced by a particular studio.
-
C.
hasStudiosIn
Indicates that an entity operates or maintains studio facilities located in a specified place or region.
-
D.
hasNearbyFictionalFeature
Indicates that an entity is located close to a fictional or imaginary geographic or structural feature.
-
E.
hasNearbyEntertainmentDistrict
Indicates that one location is situated close enough to another area known for entertainment venues (such as bars, theaters, or nightlife) to be considered nearby.
- 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_69e77e881fc08190ba1c8dc7e2a07f97 |
completed | April 21, 2026, 1:41 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 22, 2026, 8:54 a.m.