Triple
T11870745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Yehuda Street |
E282399
|
entity |
| Predicate | hasNightlifeFeature |
P43473
|
FINISHED |
| Object | bars |
—
|
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: bars | Statement: [Ben Yehuda Street, hasNightlifeFeature, bars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNightlifeFeature Context triple: [Ben Yehuda Street, hasNightlifeFeature, bars]
-
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.
offersNightlife
chosen
Indicates that a place provides opportunities for nighttime entertainment, such as bars, clubs, or evening events.
-
C.
nightlifeCharacter
Indicates a characteristic or quality associated with nightlife, such as the typical atmosphere, energy, or style of nighttime social activities.
-
D.
hasEntertainmentVenue
Indicates that an entity possesses, contains, or is associated with an entertainment venue as part of its facilities or offerings.
-
E.
hasDowntownCharacteristic
Indicates that something possesses a feature, quality, or attribute typically associated with a 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:43 p.m.