Triple
T27686728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sellier & Bellot |
E698051
|
entity |
| Predicate | isOneOfOldestAmmunitionManufacturers |
P58759
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sellier & Bellot, isOneOfOldestAmmunitionManufacturers, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfOldestAmmunitionManufacturers Context triple: [Sellier & Bellot, isOneOfOldestAmmunitionManufacturers, true]
-
A.
oneOfOldestManufacturersIn
Indicates that an entity is among the earliest-established manufacturers operating within a specified location or region.
-
B.
hasSmallCalibreGuns
Indicates that the subject is equipped with or possesses guns of relatively small calibre compared to standard or typical armaments.
-
C.
oneOfTheOldestOn
chosen
Indicates that one entity is among the earliest or longest-existing examples within the set defined by another entity.
-
D.
hasMilitarySignificanceSince
Indicates that something has held military importance or strategic value starting from a specified point in time.
-
E.
isOneOfOldestStationsInSystem
Indicates that the station is among the earliest or first-built stations within the entire system.
- F. None of above.
Provenance (3 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_69ef590df8708190af5488f0638e790c |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 2:50 p.m.