Triple
T18643579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinder U college mode |
E455748
|
entity |
| Predicate | matchingScope |
P35407
|
FINISHED |
| Object | same campus |
—
|
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: same campus | Statement: [Tinder U college mode, matchingScope, same campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchingScope Context triple: [Tinder U college mode, matchingScope, same campus]
-
A.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
-
B.
matchContext
chosen
Indicates that two or more entities are related within the same situational, conversational, or environmental setting that frames or influences their interaction.
-
C.
matchStructure
Indicates that two entities share the same structural pattern or organization, regardless of their specific content or values.
-
D.
matchTypes
Indicates that two or more entities share the same type or category according to a specified classification.
-
E.
matchLevel
Indicates the degree or extent to which two entities correspond, align, or are compatible with each other.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5500b6d7c8190b807b772980d913c |
completed | April 19, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69e478d85864819093cbad5ed9b54878 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:47 a.m.