Triple
T35468757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rexburg Idaho Temple |
E1025150
|
entity |
| Predicate | hasSealingRooms |
P201723
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Rexburg Idaho Temple, hasSealingRooms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSealingRooms Context triple: [Rexburg Idaho Temple, hasSealingRooms, yes]
-
A.
numberOfSealingRooms
Indicates the quantity of sealing rooms associated with or contained within a given entity.
-
B.
containsSecretRoomCount
Indicates that an entity has a specified number of secret rooms contained within it.
-
C.
hasStateRooms
Indicates that an entity (such as a ship, building, or facility) contains or is equipped with state rooms.
-
D.
hasSeclusion
Indicates that one entity provides, involves, or is characterized by a state or condition of privacy, isolation, or separation from others for another entity.
-
E.
hasSecretArea
Indicates that an entity contains or is associated with a hidden or restricted area not normally accessible or visible.
- 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_69f76dfa20d0819089585dc2cf653aea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0018cf6ebc8190aee6288788d0067e |
completed | May 10, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_6a001855e8588190a65840485473cf8b |
completed | May 10, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_6a0018cebf688190bbd90ac79d250182 |
completed | May 10, 2026, 5:34 a.m. |
Created at: May 3, 2026, 4:04 p.m.