Triple
T38489179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollywood Boulevard (Universal Studios Singapore) |
E918005
|
entity |
| Predicate | hasNoMajorRide |
P198516
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hollywood Boulevard (Universal Studios Singapore), hasNoMajorRide, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoMajorRide Context triple: [Hollywood Boulevard (Universal Studios Singapore), hasNoMajorRide, true]
-
A.
hasNoMajorRideVehicles
chosen
Indicates that the subject lacks any primary or significant ride vehicles associated with it.
-
B.
hasNotableRide
Indicates that an entity is associated with a particularly remarkable or well-known ride or attraction.
-
C.
hasRideCycle
Indicates that one entity is associated with, or participates in, a recurring sequence or cycle of rides or ride operations.
-
D.
hasFlatRides
Indicates that an entity (such as an amusement park or fairground) offers or includes flat rides as part of its attractions.
-
E.
hadNotableRider
Indicates that an animal, vehicle, or conveyance was ridden by a person considered historically or culturally notable.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.