Triple
T34665235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catch |
E890232
|
entity |
| Predicate | hasSisterRestaurant |
P31639
|
FINISHED |
| Object | Catch LA |
—
|
NE NERFINISHED |
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: Catch LA | Statement: [Catch, hasSisterRestaurant, Catch LA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSisterRestaurant Context triple: [Catch, hasSisterRestaurant, Catch LA]
-
A.
rivalRestaurantOf
Indicates that one restaurant competes with another restaurant in the same market or customer base.
-
B.
hasSisterResort
Indicates that one resort is formally associated with another as its sister property, typically under common ownership or branding.
-
C.
hasSister
chosen
Indicates that one entity is the sister of another entity.
-
D.
hasSiblingFacility
Indicates that one facility is related to another as a sibling facility, typically sharing a common parent organization or similar hierarchical level.
-
E.
sisterVenue
Indicates that two venues are related as peers or counterparts, typically sharing ownership, branding, or affiliation without one being subordinate to the 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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd8ccbd4c88190b13aae0673b3c821 |
completed | May 8, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69fd8ae2227c819089546f5c3629799e |
completed | May 8, 2026, 7:04 a.m. |
Created at: May 1, 2026, 2:04 a.m.