Triple
T14526286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hillman College |
E340785
|
entity |
| Predicate | hasBuildingFunctionInFiction |
P16394
|
FINISHED |
| Object | student union |
—
|
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: student union | Statement: [Hillman College, hasBuildingFunctionInFiction, student union]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingFunctionInFiction Context triple: [Hillman College, hasBuildingFunctionInFiction, student union]
-
A.
hasBuildingFunction
chosen
Indicates that a building is used for or serves a particular function or purpose.
-
B.
fictionalBuilding
Indicates that a building is imaginary or exists only within a fictional or invented context.
-
C.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
-
D.
architectInFiction
Indicates that an entity appears as an architect within a fictional work or narrative context.
-
E.
hasFeatureInFiction
Indicates that a fictional work includes or portrays a particular feature, trait, or characteristic.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea050781881909ed685d94479bf99 |
completed | April 14, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:22 a.m.