Triple
T11871307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chángzhēng |
E282412
|
entity |
| Predicate | syllable1 |
P86502
|
FINISHED |
| Object | Cháng |
—
|
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: Cháng | Statement: [Chángzhēng, syllable1, Cháng]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: syllable1 Context triple: [Chángzhēng, syllable1, Cháng]
-
A.
firstSyllable
chosen
Indicates that one entity is the first syllable occurring at the beginning of another entity (typically a word or phrase).
-
B.
secondSyllable
Indicates that the second syllable of one linguistic unit corresponds to, matches, or is identified as a particular syllable or sound in relation to another entity.
-
C.
usesSyllables
Indicates that one entity forms, expresses, or analyzes something by employing syllables as its basic units.
-
D.
syllabarySpelling
Indicates how a word or term is written using a syllabary-based writing system rather than an alphabetic one.
-
E.
unstressedSyllable
Indicates that a given syllable in a word or utterance is not emphasized or accented in pronunciation relative to other syllables.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:43 p.m.