Triple
T198374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bharat Ratna |
E4046
|
entity |
| Predicate | posthumousAwardsRestoredInYear |
P8139
|
FINISHED |
| Object | 1957 |
—
|
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: 1957 | Statement: [Bharat Ratna, posthumousAwardsRestoredInYear, 1957]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: posthumousAwardsRestoredInYear Context triple: [Bharat Ratna, posthumousAwardsRestoredInYear, 1957]
-
A.
awardReceivedYear
Indicates the specific year in which an entity received a particular award.
-
B.
canBeAwardedPosthumously
Indicates that something (such as an honor, title, or award) is eligible to be granted to a person after their death.
-
C.
goldenSpikesAwardYear
Indicates the year in which a Golden Spikes Award was given or associated with a particular recipient or event.
-
D.
awardEstablished
Indicates that an award was formally created or instituted at a specific point in time.
-
E.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
- F. None of above. chosen
Provenance (4 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25be47ea881909c296b30a0d47a65 |
completed | Feb. 28, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69a25b47481c8190add47c641c977bb9 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25be349588190aedde33d80682344 |
completed | Feb. 28, 2026, 3:07 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.