Triple
T36467714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marchenko–Pastur law |
E898463
|
entity |
| Predicate | massAtZero |
P150638
|
FINISHED |
| Object | 1 - λ for λ < 1 |
—
|
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: 1 - λ for λ < 1 | Statement: [Marchenko–Pastur law, massAtZero, 1 - λ for λ < 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: massAtZero Context triple: [Marchenko–Pastur law, massAtZero, 1 - λ for λ < 1]
-
A.
zeroMassCase
Indicates a situation or scenario in which the mass of the relevant object or system is assumed or defined to be zero.
-
B.
hasMass_kg
Indicates that an entity possesses a specific mass measured in kilograms.
-
C.
massFunction
chosen
Indicates a relationship that assigns a quantitative mass value or distribution to an entity or set of entities.
-
D.
losesMassBy
Indicates that an entity undergoes a process or interaction through which it decreases in mass.
-
E.
massParameter
Indicates a relationship where a specific mass value is assigned to or characterizes an entity as a parameter in a model or 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_69f76e58ebd88190b75d9b169b59d793 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.