Triple
T4145125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haga Palace |
E89362
|
entity |
| Predicate | hasParkFeature |
P54593
|
FINISHED |
| Object | tree-lined avenues |
—
|
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: tree-lined avenues | Statement: [Haga Palace, hasParkFeature, tree-lined avenues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParkFeature Context triple: [Haga Palace, hasParkFeature, tree-lined avenues]
-
A.
hasParking
Indicates that a place or facility provides designated parking space(s) available for use.
-
B.
hasParkStatus
Indicates that an entity holds a particular designation or status related to being a park (e.g., national park, city park, protected parkland).
-
C.
hasTypeOfPark
Indicates that an entity is associated with or classified by a specific type or category of park.
-
D.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
-
E.
hasMountingFeature
Indicates that one entity includes or provides a structural feature intended for mounting or attaching another entity.
- 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af033ef6648190adde17f943d89c78 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018c101081909070da5b11e5eb3d |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af033d94888190b34349e355b874ef |
completed | March 9, 2026, 5:28 p.m. |
Created at: March 9, 2026, 3:43 p.m.