Triple
T3061880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serve the People |
E62013
|
entity |
| Predicate | hasOriginalText |
P3563
|
FINISHED |
| Object | 为人民服务 |
—
|
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: 为人民服务 | Statement: [Serve the People, hasOriginalText, 为人民服务]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalText Context triple: [Serve the People, hasOriginalText, 为人民服务]
-
A.
originalText
chosen
Indicates that one text is the initial, unmodified version from which other versions, translations, or representations are derived.
-
B.
originalTextStatus
Indicates the relationship between a text and its current state or condition relative to its original, unmodified form.
-
C.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
D.
originallyHad
Indicates that an entity previously possessed, contained, or was associated with something before a change, loss, or transformation occurred.
-
E.
hasText
Indicates that an entity is associated with or contains a specific piece of textual 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e9f33d88190bd481cb7f18ceb91 |
completed | March 8, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69ad962326e081909d5521c3d3ea3158 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.