Triple
T28538192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calle del Cristo |
E722223
|
entity |
| Predicate | hasNearbyPlaza |
P5648
|
FINISHED |
| Object | Plaza de la Catedral |
—
|
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: Plaza de la Catedral | Statement: [Calle del Cristo, hasNearbyPlaza, Plaza de la Catedral]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyPlaza Context triple: [Calle del Cristo, hasNearbyPlaza, Plaza de la Catedral]
-
A.
hasAdjacentPlaza
Indicates that one place or structure is directly next to or bordering a plaza.
-
B.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
C.
hasNearbyParkEntrance
Indicates that one location is situated close to an entrance of a park.
-
D.
hasNearbyCommercialFacilities
Indicates that a place is located close to one or more commercial facilities, such as shops, restaurants, or other businesses.
-
E.
hasPlaza
Indicates that an entity includes, contains, or is associated with a plaza as part of its structure or grounds.
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: April 28, 2026, 3:33 a.m.