Triple
T876924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Social Democratic Party (Portugal) |
E18937
|
entity |
| Predicate | focusWhenInOpposition |
P31
|
FINISHED |
| Object | public finances |
—
|
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: public finances | Statement: [Social Democratic Party (Portugal), focusWhenInOpposition, public finances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusWhenInOpposition Context triple: [Social Democratic Party (Portugal), focusWhenInOpposition, public finances]
-
A.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
focusPeriod
Indicates the specific time span during which attention, activity, or analysis is concentrated on something.
-
C.
opposingForce
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
-
D.
facedBy
Indicates that one entity is oriented toward and directly opposite another entity, such that it is facing it.
-
E.
positionedAgainst
Indicates that one entity is placed so that it directly faces or is set opposite to another entity, often in close or contacting alignment.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acaf30a48190a10ed7fee464c444 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8d47c081909b02a53e305ccf7a |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.