Triple
T36067974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Adigar |
E1043284
|
entity |
| Predicate | officeHolderTitleInSinhala |
P201660
|
FINISHED |
| Object | Adigar |
E1043280
|
NE 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: Adigar | Statement: [First Adigar, officeHolderTitleInSinhala, Adigar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderTitleInSinhala Context triple: [First Adigar, officeHolderTitleInSinhala, Adigar]
-
A.
officeHolderTitleInMalagasy
Indicates the official title or designation of an office holder as expressed in the Malagasy language.
-
B.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
C.
officeHolderTitleInThai
Indicates the official title or designation of an office holder as expressed in the Thai language.
-
D.
officeHolderTitleInWelsh
Indicates the official title or designation of an office holder as expressed in the Welsh language.
-
E.
officeHolderTitleInAymara
Indicates the official title or designation of an office holder expressed in the Aymara language.
- F. None of above. chosen
Provenance (5 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_69f76e2fd3248190b900d9a492bf5a7a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0010e46d948190a51111b5270fade7 |
completed | May 10, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38d536f78c8190ac037c559130d678 |
completed | June 22, 2026, 6:24 a.m. |
| PD | Predicate disambiguation | batch_6a001061d34c8190bfe73f3d7c061eb7 |
completed | May 10, 2026, 4:58 a.m. |
| PDg | Predicate description generation | batch_6a0010e304a08190a4d0a4fa11a9a3b3 |
completed | May 10, 2026, 5 a.m. |
Created at: May 3, 2026, 4:08 p.m.