Triple
T21203744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jyoti Devlalikar and Arun Athavale |
E522523
|
entity |
| Predicate | hasMarriageStatus |
P105779
|
FINISHED |
| Object | troubled |
—
|
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: troubled | Statement: [Jyoti Devlalikar and Arun Athavale, hasMarriageStatus, troubled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarriageStatus Context triple: [Jyoti Devlalikar and Arun Athavale, hasMarriageStatus, troubled]
-
A.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
B.
hasCivilStatus
chosen
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
C.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
D.
spouseStatusAtMarriage
Indicates the marital status each partner held at the time their marriage to one another was formed.
-
E.
marriageLegalStatus
Indicates the legal status of a marriage relationship between entities, such as whether it is valid, invalid, pending, or dissolved under applicable law.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7343367308190b1b772d3c8e25dcb |
completed | April 21, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:19 p.m.