Triple
T27349786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maarva Andor |
E684322
|
entity |
| Predicate | funeralCustom |
P74935
|
FINISHED |
| Object | cremated and made into a funerary brick |
—
|
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: cremated and made into a funerary brick | Statement: [Maarva Andor, funeralCustom, cremated and made into a funerary brick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: funeralCustom Context triple: [Maarva Andor, funeralCustom, cremated and made into a funerary brick]
-
A.
mourningCustom
Indicates a culturally prescribed way in which people are expected to express grief and honor the dead after a loss.
-
B.
funeralType
Indicates the specific kind or category of funeral associated with an event or individual.
-
C.
hasBurialCustoms
chosen
Indicates that a group, culture, or society practices specific rituals or customs related to the treatment and burial of the dead.
-
D.
coffinDrapedWith
Indicates that a coffin is covered or adorned with a particular cloth, flag, or decorative material.
-
E.
performedAtFuneralOf
Indicates that an action or event was carried out during the funeral ceremony held for a particular individual.
- 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_69ef1480a76481908684256ddd5bfda3 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f62ba6aeb08190a6c504a508911d1f |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 11:48 a.m.