Triple
T29815212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese civilization |
E757084
|
entity |
| Predicate | hasMilitaryText |
P180336
|
FINISHED |
| Object | The Art of War |
—
|
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: The Art of War | Statement: [Chinese civilization, hasMilitaryText, The Art of War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryText Context triple: [Chinese civilization, hasMilitaryText, The Art of War]
-
A.
hasMilitaryType
Indicates that an entity is associated with or classified under a specific military category, role, or type.
-
B.
hasMilitaryClass
Indicates that an entity belongs to, is assigned to, or is categorized under a specific military class or classification.
-
C.
hasMilitarySecurity
Indicates that an entity provides, maintains, or is responsible for military protection or defense for another entity or area.
-
D.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
-
E.
hasMilitaryAssociation
Indicates a relationship in which an entity is connected or affiliated with a military organization, activity, or function.
- 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_69f2245701c88190ad42415a0956c4ed |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
| PDg | Predicate description generation | batch_69f73adfd9a081908adae6bd59dfefb9 |
completed | May 3, 2026, 12:09 p.m. |
Created at: April 29, 2026, 5:26 p.m.