Triple
T2970154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FB Beryl |
E80258
|
entity |
| Predicate | hasSights |
P45300
|
FINISHED |
| Object | iron sights |
—
|
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: iron sights | Statement: [FB Beryl, hasSights, iron sights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSights Context triple: [FB Beryl, hasSights, iron sights]
-
A.
sights
Indicates that one entity perceives or observes another entity or object using vision.
-
B.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
C.
containsAttraction
Indicates that one entity includes or encompasses an attraction (such as a point of interest, feature, or draw) within its bounds or scope.
-
D.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
E.
isMajorAttractionFor
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad997282b481909d078be0e70d9930 |
completed | March 8, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69ad960e71f8819088179d11248c6ed0 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad98379fac8190a4dfe530787703c9 |
completed | March 8, 2026, 3:39 p.m. |
Created at: March 8, 2026, 2:58 p.m.