Triple
T36958561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Railgun (Quake) |
E914248
|
entity |
| Predicate | balanceDesign |
P9277
|
FINISHED |
| Object | high damage balanced by slow refire |
—
|
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: high damage balanced by slow refire | Statement: [Railgun (Quake), balanceDesign, high damage balanced by slow refire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: balanceDesign Context triple: [Railgun (Quake), balanceDesign, high damage balanced by slow refire]
-
A.
balancedAuthorityBetween
Indicates that decision-making power or control is distributed equally or fairly among the involved entities.
-
B.
parallelDesignTo
Indicates that one design is parallel or analogous to another in structure, function, or conceptual approach.
-
C.
forceBalance
Indicates that the net forces acting on an entity or system are in equilibrium, resulting in no overall acceleration.
-
D.
balanceControl
Indicates the extent to which one entity regulates, maintains, or stabilizes the equilibrium or proportional distribution of another entity or system.
-
E.
aimsToBalance
chosen
Indicates an intention or effort by one entity to bring multiple elements, forces, or conditions into a state of equilibrium.
- 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_69f76e8c498c8190b2842db80aea8b3b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:13 p.m.