Triple
T37213478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shrek 3-D |
E922669
|
entity |
| Predicate | hasAttractionElement |
P187547
|
FINISHED |
| Object | moving seats |
—
|
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: moving seats | Statement: [Shrek 3-D, hasAttractionElement, moving seats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttractionElement Context triple: [Shrek 3-D, hasAttractionElement, moving seats]
-
A.
hasAttractionRepresentation
Indicates that one entity serves as a representation, depiction, or model of an attraction associated with another entity.
-
B.
hasAttractionType
Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
-
C.
hasAttractionBasedOn
Indicates that one entity feels an attraction toward another entity that is specifically grounded in a particular basis, criterion, or set of characteristics.
-
D.
containsAttraction
Indicates that one entity includes or encompasses an attraction (such as a point of interest, feature, or draw) within its bounds or scope.
-
E.
hasFunctionInAttraction
Indicates that one entity serves a role or performs a function within the context of attracting or drawing in another entity.
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb55dc36d08190a0634fa680e13114 |
completed | May 6, 2026, 2:53 p.m. |
Created at: May 3, 2026, 4:15 p.m.