Triple
T32186306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camassia |
E822115
|
entity |
| Predicate | riskOfConfusionWith |
P2289
|
FINISHED |
| Object | Zigadenus (deathcamas) |
—
|
NE NERFINISHED |
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: Zigadenus (deathcamas) | Statement: [Camassia, riskOfConfusionWith, Zigadenus (deathcamas)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskOfConfusionWith Context triple: [Camassia, riskOfConfusionWith, Zigadenus (deathcamas)]
-
A.
oftenConfusedWith
chosen
Indicates that one entity is frequently mistaken for or thought to be another due to similarity or ambiguity.
-
B.
associatedWithMisidentificationOf
Indicates a relationship where one entity is connected to, or involved in, the incorrect identification or labeling of another entity.
-
C.
ambiguity
Indicates that there is uncertainty, vagueness, or multiple possible interpretations in the relationship or action between entities.
-
D.
languageAmbiguity
Indicates that the meaning, interpretation, or reference of a linguistic expression is unclear or can be understood in multiple ways.
-
E.
requiresAdditionalDisambiguation
Indicates that the referenced entity or relationship is not sufficiently specific and needs further clarification or distinguishing information to avoid confusion with similar entities or meanings.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6babadb3481908b49400b3ab42a7c |
completed | May 3, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.