Triple
T22258934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philips Lighting |
E550166
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object | LIGHT |
—
|
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: LIGHT | Statement: [Philips Lighting, tickerSymbol, LIGHT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LIGHT Context triple: [Philips Lighting, tickerSymbol, LIGHT]
-
A.
Light
Light was a litigant in the U.S. Supreme Court case Light v. United States, which addressed federal authority over public lands and grazing rights.
-
B.
Light
"Light" is an emotional closing number from the rock musical *Next to Normal* that reflects themes of hope and resilience amid mental illness and family struggle.
-
C.
Light
"Light" is a novel by Swedish author Torgny Lindgren, known for its lyrical prose and exploration of human existence and morality in a stark rural setting.
-
D.
Light
"Light" is a critically acclaimed science fiction novel by M. John Harrison that intertwines space opera, quantum physics, and psychological exploration across multiple timelines.
-
E.
Light
chosen
Light is a Brazilian electric power and public services company historically linked to São Paulo’s tramway and energy infrastructure.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c4bff48190b4be83f5f7677ac8 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.