Triple
T2921742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echo Park Lotus Festival |
E78741
|
entity |
| Predicate | takesPlaceNear |
P42839
|
FINISHED |
| Object | Echo Park Lake lotus beds |
—
|
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: Echo Park Lake lotus beds | Statement: [Echo Park Lotus Festival, takesPlaceNear, Echo Park Lake lotus beds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: takesPlaceNear Context triple: [Echo Park Lotus Festival, takesPlaceNear, Echo Park Lake lotus beds]
-
A.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
-
B.
meetsNear
chosen
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or area.
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
residesNear
Indicates that one entity lives or is located in close physical proximity to another entity.
-
E.
nearDowntown
Indicates that one location is situated close to or within a short distance of a city’s downtown area.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:54 p.m.