Triple
T1171060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agent Orange |
E24912
|
entity |
| Predicate | containsContaminant |
P24582
|
FINISHED |
| Object | 2,3,7,8-tetrachlorodibenzo-p-dioxin |
—
|
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: 2,3,7,8-tetrachlorodibenzo-p-dioxin | Statement: [Agent Orange, containsContaminant, 2,3,7,8-tetrachlorodibenzo-p-dioxin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsContaminant Context triple: [Agent Orange, containsContaminant, 2,3,7,8-tetrachlorodibenzo-p-dioxin]
-
A.
containsAllergenicCompound
Indicates that the subject entity includes one or more compounds known to cause allergic reactions.
-
B.
hasSedimentsThat
Indicates that one entity contains, includes, or is associated with specific sediments described by the related entity.
-
C.
wasHeavilyPollutedDuring
Indicates that a place or environment experienced a high level of pollution during a specified time period.
-
D.
toxinType
Indicates the specific kind or category of toxin associated with an entity.
-
E.
containsMostOf
Indicates that one entity includes the majority (but not necessarily all) of the substance, elements, or components of another entity.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce972cc8190bce0b77cfda6da41 |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bbd7ff1881908c943ecdfea59e81 |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:45 p.m.