Triple
T34761239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NK model of fitness landscapes |
E1002070
|
entity |
| Predicate | KMeaning |
P181585
|
FINISHED |
| Object | number of interacting loci per locus |
—
|
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: number of interacting loci per locus | Statement: [NK model of fitness landscapes, KMeaning, number of interacting loci per locus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: KMeaning Context triple: [NK model of fitness landscapes, KMeaning, number of interacting loci per locus]
-
A.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
B.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
C.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
D.
lettersMeaning
Indicates that a set of letters or characters represents, signifies, or conveys a particular meaning or message.
-
E.
CISMeaning
Indicates that one concept, term, or symbol conveys, expresses, or stands for a particular meaning or interpretation in a given context.
- 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_69f76db0fb30819096709d43f9a1f45f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77ff804f08190b431a31e6179ace4 |
completed | May 3, 2026, 5:03 p.m. |
Created at: May 3, 2026, 3:59 p.m.