Triple
T37432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston Massacre |
E740
|
entity |
| Predicate | hasPunishment |
P3012
|
FINISHED |
| Object | branding on the thumb for convicted soldiers |
—
|
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: branding on the thumb for convicted soldiers | Statement: [Boston Massacre, hasPunishment, branding on the thumb for convicted soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPunishment Context triple: [Boston Massacre, hasPunishment, branding on the thumb for convicted soldiers]
-
A.
punishedBy
Indicates that an entity receives punishment administered by another entity.
-
B.
penaltyProvision
Indicates that a rule, contract, or law includes a clause specifying a punishment or sanction for non-compliance or violation.
-
C.
hasAwarded
Indicates that one entity has given or conferred an award to another entity.
-
D.
hasChallenge
Indicates that an entity faces, experiences, or is confronted with a particular difficulty, obstacle, or problem.
-
E.
hasConsequence
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24bb753f081909cd8b25cfb8e08af |
completed | Feb. 28, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69a24ab4a6908190b6f355415ffe7948 |
completed | Feb. 28, 2026, 1:53 a.m. |
| PDg | Predicate description generation | batch_69a24bb6881081909e7d650f2b3169d3 |
completed | Feb. 28, 2026, 1:58 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.