Triple
T876403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belém Tower |
E18926
|
entity |
| Predicate | visitorAttractionStatus |
P20989
|
FINISHED |
| Object | major tourist attraction in Lisbon |
—
|
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: major tourist attraction in Lisbon | Statement: [Belém Tower, visitorAttractionStatus, major tourist attraction in Lisbon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitorAttractionStatus Context triple: [Belém Tower, visitorAttractionStatus, major tourist attraction in Lisbon]
-
A.
visitorAttractionSince
Indicates that an entity has served as a visitor attraction starting from a specified point in time.
-
B.
visitorCenter
Indicates that a location serves as a visitor center for a place, providing information or services to visitors of that place.
-
C.
tourAccess
Indicates that an entity is permitted to participate in, enter, or make use of a specific tour.
-
D.
isAttractionFor
Indicates that one entity serves as an attraction or point of interest specifically intended for another entity (such as a person, group, or audience).
-
E.
containsAttraction
Indicates that one entity includes or encompasses an attraction (such as a point of interest, feature, or draw) within its bounds or scope.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acaf30a48190a10ed7fee464c444 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8d47c081909b02a53e305ccf7a |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab9634948190b25ea1b2e34df87d |
completed | March 1, 2026, 9:11 p.m. |
Created at: March 1, 2026, 7:39 p.m.