Triple
T314454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second United Front |
E7675
|
entity |
| Predicate | tension |
P11899
|
FINISHED |
| Object | frequent clashes between KMT and CCP despite alliance |
—
|
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: frequent clashes between KMT and CCP despite alliance | Statement: [Second United Front, tension, frequent clashes between KMT and CCP despite alliance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tension Context triple: [Second United Front, tension, frequent clashes between KMT and CCP despite alliance]
-
A.
traction
Indicates the degree to which one entity’s movement or influence effectively grips, pulls, or gains momentum relative to another entity or medium.
-
B.
tone
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
-
C.
strength
Indicates the degree of power, intensity, or effectiveness with which an entity can act on, influence, or withstand another entity or force.
-
D.
suspension
Indicates the temporary removal or halting of a privilege, activity, or status for an entity, often as a consequence or precaution.
-
E.
torque
Indicates a rotational force applied by one entity on another around a pivot or axis.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea62f830819089e94b3aa3e4e187 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e9428098819089d5950cd2c96dc4 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea08878c8190a5e8a90f620a3888 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:07 p.m.