Triple
T32981767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludlow Street |
E843818
|
entity |
| Predicate | hasNightlifeConcentration |
P166408
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Ludlow Street, hasNightlifeConcentration, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNightlifeConcentration Context triple: [Ludlow Street, hasNightlifeConcentration, high]
-
A.
hasNightlifeArea
Indicates that a place contains or is associated with an area characterized by nightlife activities such as bars, clubs, or evening entertainment venues.
-
B.
nightlifeDensity
chosen
Indicates how concentrated or abundant nightlife-related venues and activities are within a given area.
-
C.
nightlifeCharacter
Indicates a characteristic or quality associated with nightlife, such as the typical atmosphere, energy, or style of nighttime social activities.
-
D.
nightlifeRole
Indicates the specific function or position an entity holds within nightlife activities, venues, or scenes.
-
E.
hasStreetLifeCharacteristic
Indicates that an entity exhibits a particular quality, feature, or condition related to street life or street-level activity.
- 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_69f3494c6f9c8190a255409fce8b1d3b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d1dc8a108190a994bd39350129fe |
completed | May 3, 2026, 4:41 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe5f93c8190995c53dbbe380a32 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:22 a.m.