Triple
T36928461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betaab |
E913414
|
entity |
| Predicate | hasNotableLocationNamedAfterFilm |
P205643
|
FINISHED |
| Object | Betaab Valley |
E539022
|
NE 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: Betaab Valley | Statement: [Betaab, hasNotableLocationNamedAfterFilm, Betaab Valley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableLocationNamedAfterFilm Context triple: [Betaab, hasNotableLocationNamedAfterFilm, Betaab Valley]
-
A.
notableFilmingLocation
Indicates that a place served as a significant or well-known location where a film or television production was shot.
-
B.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
-
C.
hasPlaceNamesakeIn
Indicates that something is named after a particular place or location.
-
D.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
-
E.
formerFilmingLocation
Indicates that a place was once used as a filming location for a work but is no longer used for that purpose.
- F. None of above. chosen
Provenance (5 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_69f76e896c988190880c130e01303dd4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3efda85a748190a6ee43529b23fb3a |
completed | June 26, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:13 p.m.