Triple
T35003009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La-iad Phibunsongkhram |
E1009733
|
entity |
| Predicate | spouseNameInThai |
P196436
|
FINISHED |
| Object | แปลก พิบูลสงคราม |
—
|
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: แปลก พิบูลสงคราม | Statement: [La-iad Phibunsongkhram, spouseNameInThai, แปลก พิบูลสงคราม]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseNameInThai Context triple: [La-iad Phibunsongkhram, spouseNameInThai, แปลก พิบูลสงคราม]
-
A.
spouseNameInVietnamese
Indicates that the predicate specifies the name of a person's spouse as written or expressed in the Vietnamese language.
-
B.
spouseNameInKorean
Indicates that the predicate specifies the name of a person's spouse written in the Korean language.
-
C.
spouse name
Indicates that one entity is the legally recognized husband or wife of the other, specifying the partner’s name in a marital relationship.
-
D.
spouseRealName
Indicates that one person is the legally recognized spouse of another, using the spouse’s real (non-alias) name.
-
E.
spouseNameInJapanese
Indicates that one entity’s spouse is named using Japanese script or Japanese-language conventions.
- 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe349879848190bcd77e3cc3470458 |
completed | May 8, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69fe31e3cf908190b23ebc2f7fe58722 |
completed | May 8, 2026, 6:56 p.m. |
| PDg | Predicate description generation | batch_69fe349739cc8190a21c408208312e6c |
completed | May 8, 2026, 7:08 p.m. |
Created at: May 3, 2026, 4:01 p.m.