Triple
T2562622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandarin phonology |
E57275
|
entity |
| Predicate | hasOnsetTypes |
P40498
|
FINISHED |
| Object | zero onset |
—
|
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: zero onset | Statement: [Mandarin phonology, hasOnsetTypes, zero onset]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnsetTypes Context triple: [Mandarin phonology, hasOnsetTypes, zero onset]
-
A.
hasOnset
Indicates the point in time or condition at which a process, event, or state begins.
-
B.
hasEarlyOnsetForm
Indicates that the related condition, trait, or phenomenon occurs in an early-onset form, typically manifesting earlier in life than usual.
-
C.
hasLateOnsetForm
Indicates that an entity has a variant or form that manifests or becomes apparent later in life or at a relatively advanced stage.
-
D.
airedOn
Indicates that a broadcasted program or episode was shown on a specific channel, platform, or medium.
-
E.
endsOn
Indicates that one entity terminates or concludes precisely at the boundary or endpoint of another 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35c6ee88190b6eaa1841d3e99a4 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0caeb488190b0dd8e48d0f2777d |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd35b216881908f4ef32d1c1e5080 |
completed | March 7, 2026, 7:27 a.m. |
Created at: March 6, 2026, 9:48 p.m.