Triple
T29082459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meredith Quill |
E734015
|
entity |
| Predicate | deathReasonDetail |
P144
|
FINISHED |
| Object | Ego implanted a tumor in her brain |
—
|
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: Ego implanted a tumor in her brain | Statement: [Meredith Quill, deathReasonDetail, Ego implanted a tumor in her brain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathReasonDetail Context triple: [Meredith Quill, deathReasonDetail, Ego implanted a tumor in her brain]
-
A.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
B.
deathDetails
Indicates the specific circumstances, causes, and contextual information associated with an entity’s death.
-
C.
deathCharacteristic
Indicates a characteristic, attribute, or quality specifically associated with a death event or the manner in which death occurred.
-
D.
causeOfDeath
chosen
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
E.
reasonForDemise
Indicates the cause, circumstance, or factor that led to an entity’s death or termination.
- 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_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 10:56 a.m.