Triple
T23297734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tatoi Palace |
E590218
|
entity |
| Predicate | nationalizationYear |
P18594
|
FINISHED |
| Object | 1973 |
—
|
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: 1973 | Statement: [Tatoi Palace, nationalizationYear, 1973]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalizationYear Context triple: [Tatoi Palace, nationalizationYear, 1973]
-
A.
nationalisationYear
chosen
Indicates the year in which an entity was taken into state ownership or control through nationalisation.
-
B.
nationalisedOn
Indicates the date or point in time when an entity was taken into state ownership or control by a national government.
-
C.
nationalizationReason
Indicates the reason or justification for which an entity is nationalized by a state or government.
-
D.
countryEstablishedFor
Indicates that a country was founded, created, or formally established for the benefit, purpose, or use of a particular entity or group.
-
E.
statusBeforeNationalization
Indicates the condition or classification an entity had prior to being nationalized.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196d083188190abaae77dd4cf2bae |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:03 p.m.