Triple
T10504576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikkei Inc. |
E247752
|
entity |
| Predicate | acquisitionOfFinancialTimesGroupDate |
P15703
|
FINISHED |
| Object | 2015 |
—
|
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: 2015 | Statement: [Nikkei Inc., acquisitionOfFinancialTimesGroupDate, 2015]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acquisitionOfFinancialTimesGroupDate Context triple: [Nikkei Inc., acquisitionOfFinancialTimesGroupDate, 2015]
-
A.
timeOfMergerOrAcquisition
Indicates the specific point in time when a merger or acquisition event occurs between entities.
-
B.
acquisitionCompletedYear
chosen
Indicates the calendar year in which an acquisition transaction was fully completed.
-
C.
acquisitionDate
Indicates the date on which one entity formally acquires or takes ownership of another entity.
-
D.
laterAcquiredBy
Indicates that one entity was acquired by another entity at a later point in time, after some prior state or ownership.
-
E.
acquiredFranchiseYear
Indicates the year in which an entity obtained ownership or control of a franchise.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099f4dec8190a9851739c8bc9a69 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:26 p.m.