Triple
T27197955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Disney Resort |
E683654
|
entity |
| Predicate | hasOwnerStakeholder |
P1553
|
FINISHED |
| Object | Shanghai Shendi Group |
—
|
NE NERFINISHED |
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: Shanghai Shendi Group | Statement: [Shanghai Disney Resort, hasOwnerStakeholder, Shanghai Shendi Group]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOwnerStakeholder Context triple: [Shanghai Disney Resort, hasOwnerStakeholder, Shanghai Shendi Group]
-
A.
hasStakeholder
chosen
Indicates that an entity is a stakeholder of another entity, typically having an interest, involvement, or influence in its activities or outcomes.
-
B.
hasStakeholderType
Indicates that an entity is associated with a stakeholder and specifies the category or role that stakeholder fulfills in relation to the entity.
-
C.
hasCapitalOwnerRole
Indicates that an entity holds the role or status of owning capital in relation to another entity or asset.
-
D.
hasOwnerShare
Indicates that an entity holds a specified ownership stake or share in another entity or asset.
-
E.
hasIPOwner
Indicates that one entity holds ownership or legal rights over the intellectual property associated with another entity.
- 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_69eefad1fd5c8190a4a46ea6afe58bfa |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 9:35 a.m.