Triple
T3971460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ingrid Bergman: In Her Own Words |
E92343
|
entity |
| Predicate | includesMaterialType |
P1845
|
FINISHED |
| Object | personal letters |
—
|
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: personal letters | Statement: [Ingrid Bergman: In Her Own Words, includesMaterialType, personal letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesMaterialType Context triple: [Ingrid Bergman: In Her Own Words, includesMaterialType, personal letters]
-
A.
hasMaterialType
chosen
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
B.
sourceMaterialType
Indicates the type or category of material from which something originates or is derived.
-
C.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
-
D.
hasMaterialOption
Indicates that an entity can be made from, or is available in, one or more alternative materials.
-
E.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaca33e4819091957c7915857a42 |
completed | March 9, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69aef8f252b081909749d40440d372b2 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:32 p.m.