Triple
T37707660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guardian |
E939235
|
entity |
| Predicate | hasLaserRange |
P191700
|
FINISHED |
| Object | Approximately 15 blocks |
—
|
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 15 blocks | Statement: [Guardian, hasLaserRange, Approximately 15 blocks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaserRange Context triple: [Guardian, hasLaserRange, Approximately 15 blocks]
-
A.
usesLaser
Indicates that one entity employs or operates a laser in relation to another entity or context.
-
B.
hasLaserChargeTime
Indicates the duration required for a laser to charge before it can be used or activated.
-
C.
usesLaserType
Indicates that one entity employs or operates a specific type or category of laser in performing an action or function.
-
D.
hasFarDetector
Indicates that an entity is equipped with or associated with a detector positioned at a relatively large distance from a reference point or source.
-
E.
hasSignalRange
chosen
Indicates that one entity possesses a communication or detection range within which it can send, receive, or detect signals relative to another entity or area.
- 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_69f76edb49dc8190b951dce9ce6ef789 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fff59a00a881909b35b799654b3c45 |
completed | May 10, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69fff4d0a2e081909c972189b33d0128 |
completed | May 10, 2026, 3 a.m. |
Created at: May 3, 2026, 4:18 p.m.