Triple
T518077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa Caracas |
E10751
|
entity |
| Predicate | hasTypicalUse |
P2529
|
FINISHED |
| Object | day-use beach |
—
|
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: day-use beach | Statement: [Playa Caracas, hasTypicalUse, day-use beach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalUse Context triple: [Playa Caracas, hasTypicalUse, day-use beach]
-
A.
usesStandard
Indicates that one entity adopts, follows, or operates according to a specified standard defined by another entity or reference.
-
B.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
C.
eligibleUses
Indicates the types of actions, purposes, or contexts in which something is permitted or qualified to be used.
-
D.
notTypicallyUsedFor
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
E.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f19d81d48190bd65a02059fc8473 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f0151e8c81909a82b58ac0515eba |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.