Triple
T2263885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XXX Corps |
E50098
|
entity |
| Predicate | corpsNumber |
P37542
|
FINISHED |
| Object | XXX |
—
|
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: XXX | Statement: [XXX Corps, corpsNumber, XXX]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: corpsNumber Context triple: [XXX Corps, corpsNumber, XXX]
-
A.
regimentalNumber
Indicates the unique identifying number assigned to a member of a regiment, linking an individual to their specific regimental record.
-
B.
corpsColour
Indicates the specific color associated with a military corps or unit.
-
C.
administrativeNumber
Indicates that an entity is associated with a specific official identification or reference number used for administrative purposes.
-
D.
policeNumber
Indicates that an entity is associated with a specific police-related identification or reference number.
-
E.
committeeNumber
Indicates the specific numerical identifier assigned to a committee in a given context or system.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
| PDg | Predicate description generation | batch_69abc2e97eb0819084acb26cfa4e3946 |
completed | March 7, 2026, 6:17 a.m. |
Created at: March 4, 2026, 7:48 p.m.