Triple
T34639944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melian the Maia |
E889527
|
entity |
| Predicate | kinshipByMarriage |
P167266
|
FINISHED |
| Object | House of Bëor |
—
|
NE NERFINISHED |
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: House of Bëor | Statement: [Melian the Maia, kinshipByMarriage, House of Bëor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: kinshipByMarriage Context triple: [Melian the Maia, kinshipByMarriage, House of Bëor]
-
A.
connectedThroughMarriageVia
Indicates that two entities are related to each other by a marital connection that is mediated through one or more intermediate spouses or in-laws, rather than by a direct marriage between them.
-
B.
maritalRelations
Indicates a legally or socially recognized spousal relationship or marriage-based connection between two entities.
-
C.
characterRelativeByMarriage
chosen
Indicates that one character is related to another through marriage rather than by blood.
-
D.
kinshipNetwork
Indicates a familial relationship structure connecting individuals through blood, marriage, or adoption within a broader family network.
-
E.
hasNephewByMarriage
Indicates that one person is the nephew of another person through marriage rather than by blood.
- 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_69f349d724848190b63ad3407e0006d9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72291022081909c00d6aec5098b50 |
completed | May 3, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:04 a.m.