Triple
T34681053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Chinese–English Dictionary (Herbert Giles, 1892) |
E890623
|
entity |
| Predicate | scriptOfHeadwords |
P74999
|
FINISHED |
| Object | Chinese characters |
—
|
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: Chinese characters | Statement: [A Chinese–English Dictionary (Herbert Giles, 1892), scriptOfHeadwords, Chinese characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptOfHeadwords Context triple: [A Chinese–English Dictionary (Herbert Giles, 1892), scriptOfHeadwords, Chinese characters]
-
A.
partOfLexicon
Indicates that a linguistic unit (such as a word or expression) belongs to or is included within a particular lexicon or vocabulary set.
-
B.
scriptOfReferent
chosen
Indicates that a script (e.g., writing system or code) is associated with, or used to represent, a particular referent.
-
C.
spellingGimmick
Indicates a distinctive or unconventional way of spelling something used for effect or branding rather than standard orthography.
-
D.
firstWordsOf
Indicates that one entity consists of the initial word or sequence of words taken from another entity (such as a text or utterance).
-
E.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
- 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_69f349dabc008190a18999c26682ed47 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: May 1, 2026, 2:05 a.m.