Triple
T30476742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Master |
E775462
|
entity |
| Predicate | equivalentHonorific |
P90277
|
FINISHED |
| Object | Lao Tzu |
—
|
NE NERFINISHED |
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: Lao Tzu | Statement: [Old Master, equivalentHonorific, Lao Tzu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentHonorific Context triple: [Old Master, equivalentHonorific, Lao Tzu]
-
A.
alternativeHonorificFor
chosen
Indicates that one honorific title can be used as an alternative form of address for another honorific.
-
B.
honorificSense
Indicates that one entity refers to another using an honorific or respectful linguistic form.
-
C.
honorificType
Indicates the type or category of honorific or formal title associated with an entity in a given context.
-
D.
honorificIndicates
Indicates that one entity uses an honorific title or respectful form of address to refer to or address another entity.
-
E.
honorificLevel
Indicates the level of formality or respect expressed toward an entity, typically reflected in language or titles used when addressing or referring to them.
- 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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 8:12 p.m.