Triple
T28808066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SLFP |
E727433
|
entity |
| Predicate | hasPresidentOfSriLanka |
P199102
|
FINISHED |
| Object | S. W. R. D. Bandaranaike |
—
|
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: S. W. R. D. Bandaranaike | Statement: [SLFP, hasPresidentOfSriLanka, S. W. R. D. Bandaranaike]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPresidentOfSriLanka Context triple: [SLFP, hasPresidentOfSriLanka, S. W. R. D. Bandaranaike]
-
A.
presidentOfChileAtTime
Indicates that a person holds the office of President of Chile during a specified time period.
-
B.
hadPrincipalLeader
Indicates that an entity was led or headed by a primary or chief leader.
-
C.
notableFormerLeader
Indicates that the subject was once a leader of the object and is recognized as particularly significant or prominent in that former leadership role.
-
D.
wasChairmanOf
Indicates that a person held the position of chairman (leader of the board or governing body) of a specified organization or group.
-
E.
hasChiefMinisterFrom
Indicates that a political or administrative region has a chief minister whose origin, affiliation, or source is from a specified entity.
- 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69ff1f3f94fc819095955299f50ab4ce |
completed | May 9, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69ff1ea47748819082f63d9b9d9c3e65 |
completed | May 9, 2026, 11:46 a.m. |
| PDg | Predicate description generation | batch_69ff1f3ee3588190a857d1504c93be8b |
completed | May 9, 2026, 11:49 a.m. |
Created at: April 28, 2026, 6:29 a.m.