Triple
T16934808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seljuk institutions |
E410799
|
entity |
| Predicate | militaryLanguage |
P124807
|
FINISHED |
| Object | Turkic |
—
|
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: Turkic | Statement: [Seljuk institutions, militaryLanguage, Turkic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryLanguage Context triple: [Seljuk institutions, militaryLanguage, Turkic]
-
A.
militaryBranchLanguage
Indicates the language or languages officially used or primarily associated with a particular military branch.
-
B.
militaryContext
Indicates that the relationship or action occurs within a military setting, framework, or operational environment.
-
C.
militaryDomain
Indicates that the relationship or action occurs within, pertains to, or is specifically associated with the military sphere or context.
-
D.
combatantLanguage
Indicates the language used by a combatant in a conflict or competitive interaction.
-
E.
militaryUse
Indicates the use of something (such as land, facilities, equipment, or resources) for military purposes or operations.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf2899608190a6bacdce9d4ceb84 |
completed | April 18, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32d7aae948190bc238d765795688c |
completed | April 18, 2026, 7:06 a.m. |
Created at: April 10, 2026, 5:30 a.m.