Triple
T30955940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 上海商城 |
E788675
|
entity |
| Predicate | 地标属性 |
P103350
|
FINISHED |
| Object | 上海地标建筑 |
—
|
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: 上海地标建筑 | Statement: [上海商城, 地标属性, 上海地标建筑]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 地标属性 Context triple: [上海商城, 地标属性, 上海地标建筑]
-
A.
相关城市地标
Indicates a relationship where a city landmark is associated with, connected to, or relevant to a given entity or context.
-
B.
hasLandmarkProperty
chosen
Indicates that something possesses a notable or defining landmark-related characteristic or feature.
-
C.
iconicFeature
Indicates that something serves as a distinctive, widely recognized characteristic or symbol of another entity.
-
D.
isLandmarkFor
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
E.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:54 p.m.