Triple
T7656603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugh Thompson Jr. |
E173399
|
entity |
| Predicate | ethicsRole |
P9237
|
FINISHED |
| Object | lectured on military ethics |
—
|
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: lectured on military ethics | Statement: [Hugh Thompson Jr., ethicsRole, lectured on military ethics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethicsRole Context triple: [Hugh Thompson Jr., ethicsRole, lectured on military ethics]
-
A.
hasEthicalRole
chosen
Indicates that an entity holds a position, function, or responsibility defined in terms of ethical duties, norms, or moral obligations in relation to another entity or context.
-
B.
positionOnEthics
Indicates a stance, viewpoint, or opinion that an entity holds regarding ethical principles, issues, or practices.
-
C.
moralNarrativeRole
Indicates the role an entity plays within a moral storyline or ethical framing, such as being portrayed as virtuous, villainous, victimized, or morally ambiguous.
-
D.
ethicalResponsibility
Indicates a relationship in which an entity is morally obligated to act, decide, or respond in a certain way toward another entity or situation.
-
E.
typeOfEthicsLaw
Indicates that a given law pertains specifically to a particular category or type within the broader domain of ethics-related legislation.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7061cbc3c8190a917dd7e71214182 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015dd8fc8190bc5f52a12bd46209 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 3:59 p.m.