Triple
T7187682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanooki Suit |
E167610
|
entity |
| Predicate | statueStateProperty |
P75611
|
FINISHED |
| Object | Immobility |
—
|
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: Immobility | Statement: [Tanooki Suit, statueStateProperty, Immobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statueStateProperty Context triple: [Tanooki Suit, statueStateProperty, Immobility]
-
A.
hasStatue
Indicates that one entity possesses, contains, or is associated with a statue representing or located within it.
-
B.
statuePolicy
Indicates a policy or set of rules governing the creation, placement, maintenance, or treatment of statues.
-
C.
statueName
Indicates that a statue has a specific name or title associated with it.
-
D.
monumentState
Indicates that a monument is located within, or officially associated with, a particular state or state-level administrative region.
-
E.
statueSubjectRequirement
Indicates that a statue must depict or be associated with a specific required subject or type of subject.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8e2506881909fc4e81b9b79e873 |
completed | March 27, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e8b5f6508190af28e06a7959d717 |
completed | March 27, 2026, 8:29 p.m. |
Created at: March 27, 2026, 2:50 p.m.