Triple
T16167121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sari Temple |
E392332
|
entity |
| Predicate | hasNumberOfMainStories |
P995
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Sari Temple, hasNumberOfMainStories, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMainStories Context triple: [Sari Temple, hasNumberOfMainStories, 3]
-
A.
numberOfStories
chosen
Indicates the total count of levels or floors that a structure or building has.
-
B.
numberOfMainTexts
Indicates the quantity of primary or main textual components associated with an entity.
-
C.
hasMainPlotElement
Indicates that one entity serves as a central or primary plot element within the narrative of another entity.
-
D.
hasCanonicalNumberOfArticles
Indicates that an entity is associated with a standard, officially recognized count of articles that define or describe it.
-
E.
timePeriodOfPrimaryStories
Indicates the time period during which the primary stories or main narrative events of something (e.g., a work or series) take place.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb3ec4c81908d4e5c0f39a85900 |
completed | April 17, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.