Triple
T6711738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buhid language |
E153159
|
entity |
| Predicate | scriptUsedHistoricallyFor |
P2417
|
FINISHED |
| Object | inscriptions on bamboo |
—
|
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: inscriptions on bamboo | Statement: [Buhid language, scriptUsedHistoricallyFor, inscriptions on bamboo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptUsedHistoricallyFor Context triple: [Buhid language, scriptUsedHistoricallyFor, inscriptions on bamboo]
-
A.
hasHistoricalUsageIn
Indicates that something has been used or practiced within a particular historical period, context, or tradition.
-
B.
scriptUsedCurrently
Indicates that a particular writing system or script is the one presently in use for a given language, text, or context.
-
C.
areUsedSince
Indicates that entities have been in use continuously starting from a specified point in time.
-
D.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
E.
historicallyUsedFor
chosen
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
- F. None of above.
Provenance (3 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_69c68808d8d8819087369015270788fe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d121a92c8190a03f384a8aba84da |
completed | March 27, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69c6d08c5d348190a29dee668c398e70 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:06 p.m.