Triple
T13880752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Mongkut of Siam |
E333707
|
entity |
| Predicate | yearsAsMonk |
P112222
|
FINISHED |
| Object | 27 |
—
|
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: 27 | Statement: [King Mongkut of Siam, yearsAsMonk, 27]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsAsMonk Context triple: [King Mongkut of Siam, yearsAsMonk, 27]
-
A.
wasMonkOf
Indicates that a person was a member or monk belonging to a particular religious order, monastery, or monastic community.
-
B.
numberOfMonks
Indicates the quantity or count of monks associated with a given entity or context.
-
C.
numberOfMonksApprox
Indicates an approximate count or estimate of how many monks are involved or present in a given context.
-
D.
yearOfSannyasa
Indicates the specific year in which an individual formally took sannyasa (renounced worldly life and entered the renounced order).
-
E.
hasMonasticHistory
Indicates that an entity has a historical association with monastic life, institutions, or traditions.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:15 p.m.