Triple
T37056808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Objectum Sexuality |
E917212
|
entity |
| Predicate | involvesAttractionTo |
P40662
|
FINISHED |
| Object | buildings |
—
|
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: buildings | Statement: [Objectum Sexuality, involvesAttractionTo, buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesAttractionTo Context triple: [Objectum Sexuality, involvesAttractionTo, buildings]
-
A.
attracts
Indicates that one entity exerts a force or influence that draws another entity toward it.
-
B.
succeededByAttraction
Indicates that one attraction or point of interest is directly followed or replaced by another attraction in a sequence or timeline.
-
C.
connectsToAttraction
Indicates a relationship where one entity provides a direct link, route, or access to an attraction.
-
D.
unrealizedAttractionFor
Indicates a one-sided or mutual romantic or emotional attraction between entities that has not been acted upon or developed into an actual relationship.
-
E.
attractionBasedOn
chosen
Indicates a relationship where one entity is drawn to or interested in another specifically because of certain attributes, qualities, or characteristics that the latter possesses.
- 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_69f76e94d0308190a3f06890e133c88e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe8f74748c8190bd14a856c057f9f7 |
completed | May 9, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69fe8e7ed8088190929e0df67aca4de9 |
completed | May 9, 2026, 1:31 a.m. |
Created at: May 3, 2026, 4:14 p.m.