Triple
T13862078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serbo-Bulgarian War |
E333221
|
entity |
| Predicate | strengthBulgaria |
P112153
|
FINISHED |
| Object | approximately 30,000–40,000 troops |
—
|
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: approximately 30,000–40,000 troops | Statement: [Serbo-Bulgarian War, strengthBulgaria, approximately 30,000–40,000 troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: strengthBulgaria Context triple: [Serbo-Bulgarian War, strengthBulgaria, approximately 30,000–40,000 troops]
-
A.
strengthRussia
Indicates a relationship where a level, measure, or display of strength is attributed to or associated with Russia.
-
B.
strengthDenmark
Indicates a measure or characterization of Denmark’s power, influence, or robustness in a given context.
-
C.
strengthSweden
Indicates the level or degree of strength associated with Sweden in a given context.
-
D.
strength
Indicates the degree of power, intensity, or effectiveness with which an entity can act on, influence, or withstand another entity or force.
-
E.
strengthType
Indicates the specific category or nature of strength associated with an entity or relationship (e.g., physical, structural, or conceptual strength).
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:14 p.m.