Triple
T139492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinophyta |
E2819
|
entity |
| Predicate | sisterGroup |
P5990
|
FINISHED |
| Object | Cycadophyta |
—
|
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: Cycadophyta | Statement: [Pinophyta, sisterGroup, Cycadophyta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sisterGroup Context triple: [Pinophyta, sisterGroup, Cycadophyta]
-
A.
sibling
Indicates that two entities share at least one parent, making them brothers or sisters to each other.
-
B.
hasSisterOrganization
Indicates that one organization is related to another as a sister organization, typically sharing a common parent, affiliation, or parallel status within the same overarching structure.
-
C.
sisterShip
Indicates that two ships are considered counterparts or equivalents, typically of the same design, class, or series.
-
D.
subfamily
Indicates that one taxonomic group is a subfamily within a larger family, representing an intermediate rank in biological classification.
-
E.
sisterAirport
Indicates that two airports are paired or linked as counterparts, often due to geographic, operational, or organizational relationships.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257c679d88190bc71775dab2cfc64 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.