Triple
T27102217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sankara Stones |
E686471
|
entity |
| Predicate | numberInFilm |
P99268
|
FINISHED |
| Object | five |
—
|
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: five | Statement: [Sankara Stones, numberInFilm, five]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberInFilm Context triple: [Sankara Stones, numberInFilm, five]
-
A.
filmSeriesInstallmentNumber
Indicates the specific sequential position that a film occupies within a film series.
-
B.
sequenceInFilm
Indicates that one entity is a specific sequence or segment that appears within the narrative or structure of a particular film.
-
C.
mentionedInFilm
Indicates that an entity is referenced or talked about within the content of a film.
-
D.
placementInFilm
chosen
Indicates the specific position or occurrence of something within the sequence or structure of a film.
-
E.
carNumberInFilm
Indicates the specific identifying number assigned to a car as it appears within a particular film.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fe831c97c88190b27ecf100e25c2a0 |
completed | May 9, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69fe7f1b92648190b14e56bcaee5d0ca |
completed | May 9, 2026, 12:26 a.m. |
Created at: April 27, 2026, 8:48 a.m.