Triple
T23408976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waishengren |
E560012
|
entity |
| Predicate | termLiterallyMeans |
P105366
|
FINISHED |
| Object | people from outside the province |
—
|
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: people from outside the province | Statement: [Waishengren, termLiterallyMeans, people from outside the province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termLiterallyMeans Context triple: [Waishengren, termLiterallyMeans, people from outside the province]
-
A.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
B.
wordDefinition
chosen
Indicates that one entity provides the meaning or explanation of a word represented by the other entity.
-
C.
inspiredTermMeaning
Indicates that one term’s meaning is derived from, modeled after, or conceptually influenced by another term.
-
D.
tegMeaning
Indicates that one entity expresses, conveys, or stands for the meaning or semantic content of another entity.
-
E.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a50fff10819094e71fb0c11b7d95 |
completed | April 29, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69f061ed34288190a2e5e8cae03b0095 |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:38 p.m.