Triple
T30405491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mach-O binary format |
E773465
|
entity |
| Predicate | fatFileAlsoCalled |
P169173
|
FINISHED |
| Object | universal binary |
—
|
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: universal binary | Statement: [Mach-O binary format, fatFileAlsoCalled, universal binary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatFileAlsoCalled Context triple: [Mach-O binary format, fatFileAlsoCalled, universal binary]
-
A.
fatDistribution
Indicates how body fat is spatially allocated or spread across different regions of an entity.
-
B.
fatStorage
Indicates the process or state in which an organism or system accumulates and retains fat as an energy reserve.
-
C.
fatColor
Indicates the color characteristic associated with an entity’s fat or fatty tissue.
-
D.
furUse
Indicates that one entity uses the fur of another entity, typically as material or resource.
-
E.
traditionalFat
Indicates that an entity uses or contains a type or amount of fat characteristic of customary or long-established practices.
- 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_69f2248facd48190b183c3f3ca6daef7 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6861d69a08190802564e3aa7d6ea7 |
completed | May 2, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f679496c188190ba585792f987a1f4 |
completed | May 2, 2026, 10:23 p.m. |
Created at: April 29, 2026, 8:03 p.m.