Triple
T12465695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | India Street Pedestrian Mall |
E297919
|
entity |
| Predicate | hasCoveredWalkway |
P105150
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [India Street Pedestrian Mall, hasCoveredWalkway, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoveredWalkway Context triple: [India Street Pedestrian Mall, hasCoveredWalkway, yes]
-
A.
hasWalkwayPosition
Indicates the spatial or relative position of an entity along or within a walkway.
-
B.
hasWalkedRunwayFor
Indicates that one entity has modeled or appeared on the fashion runway in a show organized by another entity.
-
C.
hasWalkingPathAround
Indicates that one entity has a walking path that encircles or runs around another entity.
-
D.
isCoveredSpace
Indicates that one space or area is physically sheltered or enclosed by another structure or surface.
-
E.
hasCoveredStands
Indicates that a venue or facility includes spectator stands that are sheltered by a roof or other overhead covering.
- F. None of above. chosen
Provenance (4 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e626dbc8190ac7dcdb542ba9b0c |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d3f701c81909dd0e00251ac8553 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e5f8d04819086d1ad4d62364005 |
completed | April 10, 2026, 7:24 p.m. |
Created at: April 8, 2026, 9:56 p.m.