Triple
T20002299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carcavelos |
E494362
|
entity |
| Predicate | hasPopularUse |
P138303
|
FINISHED |
| Object | tourist destination |
—
|
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: tourist destination | Statement: [Carcavelos, hasPopularUse, tourist destination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopularUse Context triple: [Carcavelos, hasPopularUse, tourist destination]
-
A.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
-
B.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
isWidelyUsed
Indicates that something is commonly or extensively utilized across many contexts, users, or situations.
-
D.
isFamouslyUsedBy
Indicates that something is widely and notably used by a particular person, group, or entity, in a way that is broadly recognized or associated with them.
-
E.
isSometimesUsedFor
Indicates that something serves a particular purpose or function on some occasions, but not consistently or exclusively.
- F. None of above. chosen
Provenance (4 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a2e34481908a495cc5d077c41f |
completed | April 20, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:33 p.m.