Triple
T33007119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iberdrola |
E844532
|
entity |
| Predicate | acquisitionTargetCountry |
P50794
|
FINISHED |
| Object | United Kingdom |
—
|
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: United Kingdom | Statement: [Iberdrola, acquisitionTargetCountry, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acquisitionTargetCountry Context triple: [Iberdrola, acquisitionTargetCountry, United Kingdom]
-
A.
acquisitionCountry
Indicates the country in which the acquisition of an entity or asset took place.
-
B.
acquisitionTarget
chosen
Indicates that one entity is the intended or actual company or asset being acquired by another in a merger or acquisition transaction.
-
C.
acquiredCompanyCountry
Indicates the country in which the company that was acquired is located.
-
D.
countryTargeted
Indicates that a particular country is the intended object or focus of an action, operation, or influence.
-
E.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
- 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_69f3494e59f08190b9127c693e5c7e8f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6f38159d08190980ad639e08f00f4 |
completed | May 3, 2026, 7:04 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d7bee48190b94e0beb48a1d7fa |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:23 a.m.