Triple
T358663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fall of Constantinople 1453 AD |
E7599
|
entity |
| Predicate | hasDefenderStrength |
P12310
|
FINISHED |
| Object | approximately 7,000–10,000 |
—
|
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 7,000–10,000 | Statement: [Fall of Constantinople 1453 AD, hasDefenderStrength, approximately 7,000–10,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDefenderStrength Context triple: [Fall of Constantinople 1453 AD, hasDefenderStrength, approximately 7,000–10,000]
-
A.
defender
Indicates a relationship where one entity protects, guards, or supports another entity against threats, attacks, or criticism.
-
B.
isStrongerThan
Indicates that one entity possesses greater physical power, force, or effectiveness than another entity.
-
C.
defensiveStructure
Indicates a relationship where one entity functions as a structure built or used to protect, defend, or fortify another entity or area.
-
D.
combatantStrength
Indicates the relative level of power, capability, or effectiveness one combatant has in a conflict or confrontation compared to others.
-
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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebb248608190b060553219616043 |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e95aeed48190b5e48865cc964938 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2c44408190946267525c88e811 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.