Triple
T12231930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Starbrand |
E291494
|
entity |
| Predicate | hostMortalityEffect |
P27814
|
FINISHED |
| Object | transfer of Star Brand can kill or transform the host |
—
|
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: transfer of Star Brand can kill or transform the host | Statement: [Starbrand, hostMortalityEffect, transfer of Star Brand can kill or transform the host]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostMortalityEffect Context triple: [Starbrand, hostMortalityEffect, transfer of Star Brand can kill or transform the host]
-
A.
mortalityRate
Indicates the proportion of individuals in a defined population that die within a specified time period.
-
B.
effectOfDeath
chosen
Indicates the causal impact or consequences that a death has on another entity, state, or process.
-
C.
reasonForDemise
Indicates the cause, circumstance, or factor that led to an entity’s death or termination.
-
D.
massExtinctionImpact
Indicates a large-scale, catastrophic event or process that causes widespread and rapid extinction across many species or lineages.
-
E.
hostSpecies
Indicates the species that serves as the host for another organism, agent, or entity.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.