Triple
T4341527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Toungoo |
E97790
|
entity |
| Predicate | objectiveOfDefenders |
P56145
|
FINISHED |
| Object | hold Toungoo as long as possible |
—
|
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: hold Toungoo as long as possible | Statement: [Battle of Toungoo, objectiveOfDefenders, hold Toungoo as long as possible]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: objectiveOfDefenders Context triple: [Battle of Toungoo, objectiveOfDefenders, hold Toungoo as long as possible]
-
A.
objectiveOfAttackers
Indicates the target or goal that attackers aim to reach or affect through their attack.
-
B.
protectionObjective
Indicates that one entity has the goal or purpose of safeguarding, defending, or preserving another entity or its interests.
-
C.
defenderIn
Indicates that an entity serves as a defensive agent or protector within a specified context, situation, or domain.
-
D.
defender
Indicates a relationship where one entity protects, guards, or supports another entity against threats, attacks, or criticism.
-
E.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35170a6648190a15ffb21640ee478 |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b350d1649881908fa6556d875a8b4d |
completed | March 12, 2026, 11:48 p.m. |
Created at: March 12, 2026, 11:14 p.m.