Triple
T32508180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Guang |
E830856
|
entity |
| Predicate | militaryRankBeforeRevolt |
P185974
|
FINISHED |
| Object | low-ranking officer |
—
|
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: low-ranking officer | Statement: [Wu Guang, militaryRankBeforeRevolt, low-ranking officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryRankBeforeRevolt Context triple: [Wu Guang, militaryRankBeforeRevolt, low-ranking officer]
-
A.
militaryRankBeforeAccession
Indicates the military rank held by an individual prior to their accession to a particular office, position, or status.
-
B.
militaryRank
Indicates that one entity holds a specific position or level within a hierarchical military ranking system relative to another entity.
-
C.
militaryRankBeforeSultan
Indicates that one entity held a specific military rank prior to becoming a sultan.
-
D.
civilServiceRank
Indicates that one entity holds a specific rank or position within a civil service hierarchy relative to another entity or classification.
-
E.
isMilitaryRank
Indicates that one entity holds a specific position or level within a formal military hierarchy in relation to another.
- F. None of above. chosen
Provenance (4 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 1, 2026, 1 a.m.