Triple
T17758210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palantir Metropolis |
E443299
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Palantir product suite |
—
|
NE NERFINISHED |
How this triple was built (3 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: Palantir product suite | Statement: [Palantir Metropolis, partOf, Palantir product suite]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palantir product suite Context triple: [Palantir Metropolis, partOf, Palantir product suite]
-
A.
Palantir Apollo
Palantir Apollo is Palantir Technologies’ continuous delivery and deployment platform designed to manage and update complex software across diverse, distributed environments.
-
B.
Palantir Metropolis
Palantir Metropolis is a data analytics platform by Palantir Technologies designed to help financial institutions and other enterprises integrate, analyze, and model large-scale, complex data for decision-making.
-
C.
Palantir Technologies
Palantir Technologies is an American software company specializing in big data analytics platforms used by governments and large enterprises for intelligence, security, and operational decision-making.
-
D.
C3.ai
C3.ai is an enterprise artificial intelligence software company that provides a platform and applications for developing, deploying, and operating large-scale AI, predictive analytics, and IoT solutions for businesses and governments.
-
E.
Rubin Science Platform
Rubin Science Platform is an integrated, cloud-based environment that enables scientists to access, analyze, and collaborate on data from the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Palantir product suite Target entity description: The Palantir product suite is a collection of data integration and analytics platforms designed to help organizations aggregate, analyze, and operationalize large-scale data for decision-making.
-
A.
Palantir Apollo
Palantir Apollo is Palantir Technologies’ continuous delivery and deployment platform designed to manage and update complex software across diverse, distributed environments.
-
B.
Palantir Metropolis
chosen
Palantir Metropolis is a data analytics platform by Palantir Technologies designed to help financial institutions and other enterprises integrate, analyze, and model large-scale, complex data for decision-making.
-
C.
Palantir Technologies
Palantir Technologies is an American software company specializing in big data analytics platforms used by governments and large enterprises for intelligence, security, and operational decision-making.
-
D.
C3.ai
C3.ai is an enterprise artificial intelligence software company that provides a platform and applications for developing, deploying, and operating large-scale AI, predictive analytics, and IoT solutions for businesses and governments.
-
E.
Rubin Science Platform
Rubin Science Platform is an integrated, cloud-based environment that enables scientists to access, analyze, and collaborate on data from the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.
- F. None of above.
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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841fe97881908f4df503fb781763 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 10:10 a.m.